CVE-2025-1716VulnerabilityPublished 26 Feb 2025Updated 29 Dec 2025

CVE-2025-1716: mmaitre314 picklescan · Incomplete List of Disallowed Inputs

Affects mmaitre314 picklescanSource CVE Database V5

Not known to be exploited · CVSS 5.3 Medium.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 4.0 base score

5.3Medium

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

EPSS: 1.7% chance of exploitation in 30 days – higher than 77% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N

Attack Vector: Network
Attack Complexity: Low
Attack Requirements: None
Privileges Required: None
User Interaction: Passive
Vulnerable system confidentiality: None
Vulnerable system integrity: Low
Vulnerable system availability: None
Subsequent system confidentiality: None
Subsequent system integrity: None
Subsequent system availability: None

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

Attack Vector: Network: The vulnerable system is bound to the network stack and the set of possible attackers extends beyond the other options listed below, 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: The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.
Attack Requirements: None: The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.
User Interaction: Passive: Successful exploitation of this vulnerability requires limited interaction by the targeted user with the vulnerable system and the attacker’s payload. These interactions would be considered involuntary and do not require that the user actively subvert protections built into the vulnerable system.
Vulnerable system confidentiality: None: There is no loss of confidentiality within the Vulnerable System.
Vulnerable system integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact to the Vulnerable System.
Vulnerable system availability: None: There is no impact to availability within the Vulnerable System.
Subsequent system confidentiality: None: There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.
Subsequent system integrity: None: There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable System.
Subsequent system availability: None: There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.

Definitions: FIRST CVSS v4.0 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 26 Feb 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: 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 2026-10-25.

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.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC 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
PyPIpicklescan`pkg:pypi/picklescan`Other threats	Affected =0.0.1	Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

To mitigate CVE-2025-1716, European organizations should immediately upgrade picklescan to version 0.0.21 or later, where 'pip' is correctly treated as an unsafe global. Until patches are applied, organizations should avoid scanning untrusted or third-party Pickle models with vulnerable picklescan versions. Implement strict model provenance and validation policies to reduce the risk of malicious inputs. Consider sandboxing the scanning environment to limit the impact of potential code execution during scans. Additionally, monitor network traffic and system logs for unusual pip activity or package installations triggered during scanning. Security teams should review and harden CI/CD pipelines that incorporate picklescan to prevent exploitation. Finally, raise awareness among data scientists and developers about the risks of deserializing untrusted Pickle data and encourage the use of safer serialization formats where possible.

Description

picklescan before 0.0.21 does not treat 'pip' as an unsafe global. An attacker could craft a malicious model that uses Pickle to pull in a malicious PyPI package (hosted, for example, on pypi.org or GitHub) via `pip.main()`. Because pip is not a restricted global, the model, when scanned with picklescan, would pass security checks and appear to be safe, when it could instead prove to be problematic.

Impact

For European organizations, the impact of CVE-2025-1716 can be significant in environments where picklescan is used to validate machine learning models before deployment. Successful exploitation could lead to arbitrary code execution on systems performing the scan, potentially compromising build pipelines, continuous integration environments, or production servers. This could result in unauthorized access, data theft, or further malware deployment. Organizations relying on Python-based ML workflows and automated security scanning are at risk of supply chain compromise through malicious model uploads. The medium severity score reflects that while exploitation requires user interaction (scanning the malicious model), the lack of privilege requirements and network attack vector make it feasible in environments where untrusted models are scanned. The vulnerability could disrupt trust in ML model validation processes and introduce risks to data confidentiality and system integrity. European sectors with high adoption of Python ML tools, such as finance, automotive, and research institutions, may face elevated risks.

CWE-184Incomplete List of Disallowed Inputs (opens in a new tab)
Base weaknessOWASP Top 10 A03:2021: Injection (opens in a new tab)
The product implements a protection mechanism that relies on a list of inputs (or properties of inputs) that are not allowed by policy or otherwise require other action to neutralize before additional processing takes place, but the list is incomplete.
Implementation · Input Validation
Do not rely exclusively on detecting disallowed inputs. There are too many variants to encode a character, especially when different environments are used, so there is a high likelihood of missing some variants. Only use detection of disallowed inputs as a mechanism for detecting suspicious activity.
Attack patterns
Double Encoding (opens in a new tab)
Command Delimiters (opens in a new tab)
Flash Injection (opens in a new tab)
Using Leading 'Ghost' Character Sequences to Bypass Input Filters (opens in a new tab)
Exploiting Multiple Input Interpretation Layers (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 30 Dec 2025, 23:50 UTC

WeaknessesCWE-184

Technical details

References

Community reviews

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