Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2026-31932 is a high-severity Inefficient Algorithmic Complexity (CWE-407) vulnerability in Oisf Suricata. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked at the 19th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SC-5 (Denial-of-service Protection) and SC-6 (Resource Availability) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-31932 affects Suricata, an open-source network intrusion detection system (IDS), intrusion prevention system (IPS), and network security monitoring (NSM) engine. The vulnerability stems from an inefficiency in KRB5 buffering that causes performance degradation. It impacts versions of Suricata prior to 7.0.15 and 8.0.4, and has been assigned CWE-407 (incomplete cleanup) with a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H).
The vulnerability can be exploited remotely over the network by unauthenticated attackers with low complexity and no user interaction required. By sending crafted traffic that triggers the inefficient KRB5 buffering, attackers can induce significant performance degradation, leading to high availability impact such as denial-of-service on the affected Suricata instance. There is no impact on confidentiality or integrity.
Advisories recommend upgrading to Suricata versions 7.0.15 or 8.0.4, where the issue has been patched. Detailed information is available in the GitHub Security Advisory at https://github.com/OISF/suricata/security/advisories/GHSA-rp9m-jcpw-hggr and the Open Information Security Foundation Redmine issue at https://redmine.openinfosecfoundation.org/issues/8305.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18239
Vulnerability Data
Suricata is a network IDS, IPS and NSM engine. Prior to versions 7.0.15 and 8.0.4, inefficiency in KRB5 buffering can lead to performance degradation. This issue has been patched in versions 7.0.15 and 8.0.4.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.9
Mitigating Controls (NIST 800-53 r5) AI
Denial-of-service protection directly reduces the impact of resource exhaustion triggered by worst-case algorithmic inputs.
Resource availability allocation limits blast radius when an inefficient algorithm is forced into its worst case.
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.
Secure SDLC practices (code review, complexity analysis, safe algorithm selection) prevent introduction of exploitable worst-case behavior.
Runtime monitoring of software and resources can detect the performance impact of triggered worst-case complexity.
Identifying and recording algorithmic-complexity vulnerabilities directly addresses the root cause before exploitation.
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.
Security testing can uncover performance issues stemming from algorithmic complexity.
Redundancy of processing facilities can absorb resource exhaustion from inefficient algorithms.
Monitoring activities can identify anomalous resource consumption indicative of algorithmic complexity attacks.
Secure development life cycle includes design reviews that can catch inefficient algorithms before deployment.
Secure system architecture principles encourage selection of algorithms with acceptable worst-case complexity.
Secure coding practices can include guidelines to avoid or mitigate inefficient algorithms.