How severe is GHSA-mq84-hjqx-cwf2?

No CVSS score has been assigned to GHSA-mq84-hjqx-cwf2 yet. Review the advisory details and affected package list to assess your exposure.

Which packages are affected by GHSA-mq84-hjqx-cwf2?

GHSA-mq84-hjqx-cwf2 affects the following packages: keras (PyPI). Ecosystems affected: PyPI.

How do I fix GHSA-mq84-hjqx-cwf2?

Update keras to 3.12.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-mq84-hjqx-cwf2 is resolved across your whole dependency graph.

How do I detect GHSA-mq84-hjqx-cwf2 in my PyPI dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for keras. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

How do I mitigate GHSA-mq84-hjqx-cwf2 if there is no patch (or I can't update yet)?

If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

How does O3 Security protect against GHSA-mq84-hjqx-cwf2?

O3 pinpoints whether GHSA-mq84-hjqx-cwf2 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Is GHSA-mq84-hjqx-cwf2 actively exploited in the wild?

No public exploit code has been indexed for GHSA-mq84-hjqx-cwf2 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for GHSA-mq84-hjqx-cwf2?

GHSA-mq84-hjqx-cwf2 has an EPSS (Exploit Prediction Scoring System) score of 0.2%, placing it in the 14th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is GHSA-mq84-hjqx-cwf2?

GHSA-mq84-hjqx-cwf2 is classified as Deserialization of Untrusted Data (CWE-502). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation. This is a high-impact weakness class that often enables remote code execution or data exposure.

When was GHSA-mq84-hjqx-cwf2 published, and has it been updated?

GHSA-mq84-hjqx-cwf2 was published on October 29, 2025 and was last updated on March 12, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍 PyPI

GHSA-mq84-hjqx-cwf2

Keras is vulnerable to arbitrary local file loading and Server-Side Request Forgery

Also known asCVE-2025-12058 GHSA-qg93-c7p6-gg7f

Published

Oct 29, 2025

Updated

Mar 12, 2026

Affected

1 pkg

Patched

1 / 1

Exploits

None indexed

EPSS Exploitation Probability

via FIRST.org ↗

0.2%probability of exploitation in next 30 days

Lower Risk14th percentile+0.15%

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

Blast Radius

1 pkg affected

🐍keras

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

The Keras.Model.load_model method, including when executed with the intended security mitigation safe_mode=True, is vulnerable to arbitrary local file loading and Server-Side Request Forgery (SSRF).

This vulnerability stems from the way the StringLookup layer is handled during model loading from a specially crafted .keras archive. The constructor for the StringLookup layer accepts a vocabulary argument that can specify a local file path or a remote file path.

Arbitrary Local File Read: An attacker can create a malicious .keras file that embeds a local path in the StringLookup layer's configuration. When the model is loaded, Keras will attempt to read the content of the specified local file and incorporate it into the model state (e.g., retrievable via get_vocabulary()), allowing an attacker to read arbitrary local files on the hosting system.
Server-Side Request Forgery (SSRF): Keras utilizes tf.io.gfile for file operations. Since tf.io.gfile supports remote filesystem handlers (such as GCS and HDFS) and HTTP/HTTPS protocols, the same mechanism can be leveraged to fetch content from arbitrary network endpoints on the server's behalf, resulting in an SSRF condition.

The security issue is that the feature allowing external path loading was not properly restricted by the safe_mode=True flag, which was intended to prevent such unintended data access.

Affected Packages

1 total 1 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`keras`	all versions	3.12.0

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for keras. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update keras to 3.12.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-mq84-hjqx-cwf2 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-mq84-hjqx-cwf2 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-mq84-hjqx-cwf2. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

The Keras.Model.load_model method, including when executed with the intended security mitigation safe_mode=True, is vulnerable to arbitrary local file loading and Server-Side Request Forgery (SSRF). This vulnerability stems from the way the StringLookup layer is handled during model loading from a specially crafted .keras archive. The constructor for the StringLookup layer accepts a vocabulary argument that can specify a local file path or a remote file path. * Arbitrary Local File Read: An attacker can create a malicious .keras file that embeds a local path in the StringLookup layer's c

O3 Security · Impact-Aware SCA

Is GHSA-mq84-hjqx-cwf2 in your dependencies?

O3 detects GHSA-mq84-hjqx-cwf2 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

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