HOL LogoGuard

Explore HOL

  • HOL home
  • AI agent registry
  • AI plugins
  • Open standards
  • HOL members
  • Sponsor HOL
  • Advertise with HOL

Guard product

  • Guard overviewLocal security and control for AI agents and the tools they use.
  • FeaturesRuntime protection, policy routing, review, and evidence.

Explore Guard

  • Product previewWalk through Guard surfaces in read-only demo mode.
  • ComparisonCompare Guard with native controls and AI security vendors.

AI tools

  • All AI toolsEvery supported AI tool and how Guard applies policy to it.
  • Codex
  • Claude Code
  • Cursor
  • Antigravity CLI
  • OpenCode
  • Hermes
  • OpenClaw
  • GitHub Copilot CLI
  • Antigravity
  • Kimi
  • Grok
  • Pi / Oh My Pi
  • Zcode

Extensions

  • All extensionsBrowse command and MCP coverage with owners and stated limits.
  • Command coverageShell command protection across clouds, databases, backups, and packages.
  • MCP server coverageSee how Guard maps risk state across MCP tools and servers.
  • Core safetyThe safety floor listings that ship with Guard.
  • Data and resilienceBackup and storage command protection.
  • Cloud and infrastructureAWS, Azure, GCP, Kubernetes, and more.

Security

  • AI security hubSecurity research, advisories, and agent safety coverage.
  • AI tool securitySecurity profiles for each supported coding agent.
  • Safe labsHands-on attack simulations with safe boundaries.
  • Redacted warningsReal blocked actions with sensitive details removed.
  • AdvisoriesCoordinated disclosure reports for AI tooling.
  • Active CVEsSearch active CVEs affecting AI tooling.

Learn

  • Security guidesPractical guides for securing AI agent workflows.
  • DocsInstall, configure, and operate Guard with confidence.
  • ResearchPublished security research, benchmarks, and methodology.

Community

  • ReleasesVersion history, shipped changes and upgrade notes.
  • ContributorsThe people and contributions behind HOL Guard.
  • AffiliatesShare Guard with your audience and earn from referrals.
  • SponsorFund agreed research, implementation and shared testing through the HOL Partner Program.
  • AdvertiseCompare README logo placements, previews and monthly prices, or promote a plugin or extension.
PricingEnterpriseOpen AppInstall Guard
  1. Guard
  2. Security
  3. CVEs
  4. CVE 2024 58399 llamacpp before b2731 out of bounds read via gguf
HOL Guard

Public security guidance for teams protecting AI harnesses, MCP servers, skills, prompts, and local tool execution.

Install Guard

AI Security

  • Prompt injection
  • MCP security
  • OWASP MCP mapping
  • Supply chain

Resources

  • Trust packet
  • Harness setup
  • Redacted warnings
  • Safe labs

Product

  • Install Guard
  • Pricing
  • Open dashboard
Guard
  • Guard Overview
  • Releases
  • Contributors
  • Install Guard
  • Pricing
Docs
  • Documentation Index
  • Developer Hub
  • API Reference
  • Root OpenAPI
  • Registry OpenAPI
  • Run in Postman
  • Standards
  • Submit ERC-8004 Contract
  • Feature Your Agent
Best Plugins
  • Browse Plugins
  • Plugin Launches
  • Best Claude Plugins
  • Best Codex Plugins
  • Best Grok Plugins
  • Best Kimi Plugins
  • Best DeepSeek Plugins
  • Best Antigravity Plugins
  • Best MCP Servers
  • Best Cursor Plugins
  • Best OpenCode Plugins
Best Agents
  • Best ERC-8004 Agents
  • Best Virtuals Agents
  • Best MCP Servers
  • Best A2A Agents
  • Best x402 Payable
  • All Categories
Community
  • Telegram
  • X
More
  • About HOL
  • Sponsor
  • Advertise
  • Contact
  • Blog
  • GitHub
  • Privacy
  • Terms of Service
Settings

Copyright © 2026 HOL DAO LLC. All rights reserved.

Back to active CVEs
Medium · CVSS 6.9CVE-2024-58399

llama.cpp before b2731 Out-of-Bounds Read via GGUF Tensor OffsetsCVE-2024-58399

Answer in brief

CVE-2024-58399 records a Medium severity (CVSS 6.9) vulnerability in llama.cpp before b2731 Out-of-Bounds Read via GGUF Tensor Offsets. The current sources do not mark it as known exploited. The current feed maps ggml-org/llama.cpp (generic). Check affected ranges and fixed versions before updating.

Analysis pending evidence review

HOL Guard separates source facts from reviewed analysis. See the methodology.

Published Oct 27, 2026Updated Oct 27, 2026Source checked Oct 27, 2026First seen by HOL Oct 27, 2026Material review Oct 27, 2026
Upstream Advisory

Key facts

Risk
Medium · CVSS 6.9
Exploitation
Not marked as known exploited
Affected software
1 mapped package or product
Fix availability
Available

Why this deserves its current priority

CVSS is 6.9. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.

Analysis status

Analysis pending evidence review

Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.

Affected scope and exposure questions

The current feed maps ggml-org/llama.cpp (generic). Check affected ranges and fixed versions before updating.

Mapped affected packages and fixed versions
PackageAffected rangeFixed version
ggml-org/llama.cppgeneric>=b1046 <b2731b2731

Recommended response

  1. 1Check inventory. Check lockfiles and deployed manifests for ggml-org/llama.cpp.
  2. 2Review the reported fix. Update ggml-org/llama.cpp to b2731 if you use the affected versions. Test the change in a non-production environment first.

Evidence timeline and material changes

  1. Published upstream

    Oct 27, 2026

    Evidence: source:cvelist:source_dates:source-dates:record

  2. Source modified

    Oct 27, 2026

    Evidence: source:cvelist:source_dates:source-dates:record

  3. First seen by HOL

    Oct 27, 2026

Sources and claim methodology

  • GitHub security advisorygithub.com
  • GitHub security advisorygithub.com
  • GitHub security advisorygithub.com
  • GitHub security advisorygithub.com
  • GitHub security advisorygithub.com
  • Source referencevulncheck.com
Upstream source description

llama.cpp before b2731 contains an out-of-bounds read vulnerability in llama_model_loader that allows attackers to read memory outside the mapped model file via crafted GGUF tensor offsets. Attackers can supply a crafted or truncated GGUF model file with arbitrary 64-bit tensor offsets to crash the process or load adjacent process memory as model weights.

Quoted source text, attributed separately from HOL analysis.

Related CVEs

  • llama.cpp before b3701 Out-of-Bounds Read in llama_decode via Token IDsSame ggml-org/llama.cpp package
  • llama.cpp before b5649 Heap Out-of-Bounds Read via llama_vocab::impl::print_infoSame ggml-org/llama.cpp package
  • llama.cpp b5899 before b10261 Heap Out-of-Bounds Write via plamo2 TokenizerSame ggml-org/llama.cpp package
  • llama.cpp b10398 before b11301 Integer Overflow in gguf_init_from_readerSame ggml-org/llama.cpp package
  • llama.cpp b5854 before b11275 Integer Overflow in gguf_init_from_readerSame ggml-org/llama.cpp package
  • Tencent RapidJSON Regex stream.h Take out-of-boundsAlso CWE-125

Record context

Vulnerability class
Buffer Overflow
EPSS
Not reported
CWE IDs
CWE-125
Source
CVE List V5
Source checked
Oct 27, 2026
References
6 linked sources
Open source record