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Security audit

Llama Llama3

Security checks for vulnerabilities and agentic risk

Overview

This skill is a coherent guide for running Llama models through a local Ollama fleet, with ordinary installation and local API examples but some supply-chain caution around an unpinned PyPI package.

Install only if you intend to run `ollama-herd` as a local fleet router. Prefer a virtual environment, avoid root or administrator shells, consider pinning or reviewing the package version, and do not send sensitive prompts or audio files unless you trust every device in the fleet and its local logs.

A.I.G

Vulnerability Patterns
  • Insecure DependenciesIntroduces malicious components through unsafe dependency sources
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
Findings (1)

T08 · Insecure Dependencies

Warning
Location
SKILL.md:29
Finding

Unpinned Third-Party Package Installation

Content
View full analysis
Remediation
View remediation
" ``` 2. Publish a requirements or constraints file containing cryptographic hashes and require hash validation: ```text ollama-herd== \ --hash=sha256: ``` Install it with: ```bash python3 -m pip install --require-hashes -r requirements.txt ``` 3. Verify and update the pinned version through a controlled dependency-review process rather than automatically selecting the latest release. 4. Recommend installation in a dedicated virtual environment under a non-privileged account: ```bash python3 -m venv .venv . .venv/bin/activate python3 -m pip install --require-hashes -r requirements.txt ``` 5. Explicitly warn users not to run pip or the package commands with administrator or root privileges. 6. Where practical, document the expected package publisher, source repository, release provenance, and artifact digest so users can independently validate the dependency. ]]>

SkillSpector

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (6)

External Script Fetching

High
Category
Supply Chain
Confidence
90% confidence
Finding

Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.

Content

Scanner excerpt · SKILL.md (reported line 95)May include surrounding context.

bash
# Models loaded in memory right now
curl -s http://localhost:11435/api/ps | python3 -m json.tool

# All models available across the fleet
curl -s http://localhost:11435/api/tags | python3 -m json.tool

External Script Fetching

High
Category
Supply Chain
Confidence
90% confidence
Finding

Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.

Content

Scanner excerpt · SKILL.md (reported line 98)May include surrounding context.

curl -s http://localhost:11435/api/ps | python3 -m json.tool

All models available across the fleet

curl -s http://localhost:11435/api/tags | python3 -m json.tool

text

## Monitor Llama performance

External Script Fetching

High
Category
Supply Chain
Confidence
90% confidence
Finding

Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.

Content

Scanner excerpt · SKILL.md (reported line 105)May include surrounding context.

bash
# Recent request traces — see latency, tokens, which node handled each request
curl -s "http://localhost:11435/dashboard/api/traces?limit=10" | python3 -m json.tool

# Fleet health — 15 automated checks
curl -s http://localhost:11435/dashboard/api/health | python3 -m json.tool

External Script Fetching

High
Category
Supply Chain
Confidence
90% confidence
Finding

Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.

Content

Scanner excerpt · SKILL.md (reported line 108)May include surrounding context.

curl -s "http://localhost:11435/dashboard/api/traces?limit=10" | python3 -m json.tool

Fleet health — 15 automated checks

curl -s http://localhost:11435/dashboard/api/health | python3 -m json.tool

text

Web dashboard at `http://localhost:11435/dashboard` — live view of all nodes, queues, and models.

External Transmission

Medium
Category
Data Exfiltration
Confidence
60% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 50)May include surrounding context.

print(chunk.choices[0].delta.content or "", end="")

text

### curl (Ollama format)

```bash
curl http://localhost:11435/api/chat -d '{

External Transmission

Medium
Category
Data Exfiltration
Confidence
60% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 122)May include surrounding context.

Image generation

bash
curl http://localhost:11435/api/generate-image \
  -d '{"model": "z-image-turbo", "prompt": "a llama in the mountains", "width": 512, "height": 512}'

Static analysis

No suspicious patterns detected.