Critical Alert 4 Active Exploits Detected Today

CVE-2026-93952 Arista VeloCloud Orchestrator Improper Input Validation Vulnerability →
CVE-2026-94127 F5 BIG-IP APM Heap-based Buffer Overflow Vulnerability →
CVE-2026-93616 Check Point Multiple Products Path Traversal Vulnerability →
CVE-2026-85102 Check Point Multiple Products Improper Certificate Validation Vulnerability →
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CVE-2026-57173NVD

Vulnerability Summary

vLLM is an inference and serving engine for large language models. Prior to 0.24.0, the input_audio handling path for /v1/chat/completions calls AudioMediaIO.load_bytes or AudioMediaIO.load_file without passing VLLM_MAX_AUDIO_DECODE_DURATION_S to the shared audio decoder. An unauthenticated client can therefore submit a small compressed audio input that expands into a very large float32 PCM allocation, bypassing the duration guard already used by /v1/audio/transcriptions and causing an out-of-memory worker crash. Inline data URLs reach this path without being bounded by VLLM_AUDIO_FETCH_TIMEOUT. The issue affects deployments serving an audio-capable model, and authentication changes only the deployment-specific reachability. This issue is fixed in version 0.24.0.
Severity Level
MEDIUM(6.5)
Published Date
Sep 16, 2026
Last Modified
Sep 18, 2026
Exploitation Status
No confirmed exploitation yet
EPSS Score (30-Day)
0.66%Probability
Root Weakness (CWE)
Refer to the official MITRE database for detailed architectural specifications regarding this weakness.
CVSS v3.1 Base Metrics — Score 6.5 (MEDIUM)
Attack VectorNetwork
Attack ComplexityLow
Privileges RequiredLow
User InteractionNone
ScopeUnchanged
ConfidentialityNone
IntegrityNone
AvailabilityHigh

Affected & Patched Versions

Affected Versions
  • vllm-project vllm >= < 0.24.0
Patched Versions
Not provided by cveorg for this CVE.
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