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lbeurerkellner

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Submissions

Skill-Inject: Measuring Agent Vulnerability to Skill File Attacks

arxiv.org
1 points·by lbeurerkellner·4 miesiące temu·1 comments

Snyk Agent Scan: Security scanner for AI agents, MCP servers and agent skills

github.com
2 points·by lbeurerkellner·4 miesiące temu·0 comments

MCP-Scan: A Security scanner for AI agents, MCP servers and agent skills

github.com
3 points·by lbeurerkellner·5 miesięcy temu·0 comments

Technical Report: Exploring the Emerging Threats of the Agent Skill Ecosystem

github.com
3 points·by lbeurerkellner·5 miesięcy temu·0 comments

MCP-Scan: Constrain, log and scan your MCP server for security vulnerabilities

github.com
2 points·by lbeurerkellner·9 miesięcy temu·0 comments

comments

lbeurerkellner
·8 miesięcy temu·discuss
Interesting report. Though, I think many of the attack demos cheat a bit, by putting injections more or less directly in the prompt (here via a website at least).

I know it is only one more step, but from a privilege perspective, having the user essentially tell the agent to do what the attackers are saying, is less realistic then let’s say a real drive-by attack, where the user has asked for something completely different.

Still, good finding/article of course.
lbeurerkellner
·8 miesięcy temu·discuss
Everybody should try. It helps a ton to demystify the relatively simple but powerful underpinning of how modern agents work.

You can get quite far quite quickly. My toy implementation [1] is <600 LOC and even supports MCP.

[1] https://github.com/lbeurerkellner/agent.py
lbeurerkellner
·11 miesięcy temu·discuss
This is way more common with popular MCP server/agent toolsets than you would think.

For those interested in some threat modeling exercise, we recently added a feature to mcp-scan that can analyze toolsets for potential lethal trifecta scenarios. See [1] and [2].

[1] toxic flow analysis, https://invariantlabs.ai/blog/toxic-flow-analysis

[2] mcp-scan, https://github.com/invariantlabs-ai/mcp-scan