CVE-2024-23342
Tlsfuzzer Ecdsa ≤ 0.18.0
Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2024-23342 is a high-severity Observable Discrepancy (CWE-203) vulnerability in Tlsfuzzer Ecdsa. Its CVSS base score is 7.4 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data Obfuscation (T1001); ranked in the top 38% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to IA-6 (Authentication Feedback) and SA-11 (Developer Testing and Evaluation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0448
Vulnerability Data
The `ecdsa` PyPI package is a pure Python implementation of ECC (Elliptic Curve Cryptography) with support for ECDSA (Elliptic Curve Digital Signature Algorithm), EdDSA (Edwards-curve Digital Signature Algorithm) and ECDH (Elliptic Curve Diffie-Hellman). Versions 0.18.0 and prior are vulnerable to…
more
the Minerva attack. As of time of publication, no known patched version exists.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 1 hardening rule · 1 OS baseline
V11.2.4
Mitigating Controls (NIST 800-53 r5) AI
Obscures authentication feedback so that success/failure differences are not observable to attackers.
Developer testing can include timing analysis or side-channel test cases that reveal observable timing discrepancies.
Covert channel analysis directly identifies timing channels that could leak information.
Requires error messages to avoid revealing exploitable details, directly stopping observable response discrepancies.
Engineering principles can mandate constant-time algorithms and side-channel resistance so timing discrepancies are never introduced.
Requiring approved cryptographic modules and algorithms implicitly demands implementations free of observable timing leaks.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Runtime monitoring of hardware/software behavior can detect anomalous timing patterns that indicate covert channels.
Vulnerability identification processes can surface timing-channel weaknesses during design or code analysis.
Secure SDLC practices directly prevent observable response discrepancies via consistent error handling and timing.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.