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sandeep_kamble

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投稿

PROMPTPurify: 14 MB CPU-only prompt-injection guard (benchmarked vs. OSS guard)

github.com
1 ポイント·投稿者 sandeep_kamble·先月·0 コメント

[untitled]

1 ポイント·投稿者 sandeep_kamble·先月·0 コメント

[untitled]

1 ポイント·投稿者 sandeep_kamble·2 か月前·0 コメント

Sandyaa: Recursive-LLM source code auditor that writes exploitable PoCs

github.com
2 ポイント·投稿者 sandeep_kamble·3 か月前·1 コメント

[untitled]

1 ポイント·投稿者 sandeep_kamble·4 か月前·0 コメント

[untitled]

1 ポイント·投稿者 sandeep_kamble·5 か月前·0 コメント

GeminiJack: A prompt-injection challenge demonstrating real-world LLM abuse

geminijack.securelayer7.net
1 ポイント·投稿者 sandeep_kamble·7 か月前·1 コメント

Show HN: AI Agent for Microsoft Grap Red Team Framework

github.com
3 ポイント·投稿者 sandeep_kamble·9 か月前·0 コメント

コメント

sandeep_kamble
·先月·議論
[flagged]
sandeep_kamble
·3 か月前·議論
Sandyaa is an open-source autonomous source code auditor. Point it at a directory or a git URL and it runs end-to-end: builds context, detects vulnerabilities, writes runnable proof-of-concepts, and emits a findings/ folder where every claim in evidence.json is linked back to a file and line. why to wait for Mythos :))
sandeep_kamble
·7 か月前·議論
A few days ago, a research team disclosed GeminiJack, a prompt-injection vulnerability affecting LLM-powered applications.

I recreated the same class of vulnerability as an interactive challenge to demonstrate how subtle prompt injection flaws can bypass guardrails, alter model behavior, and lead to unintended actions in real systems.

This is not a write-up, but a hands-on challenge. If you’re working with LLM apps, RAG pipelines, or AI agents, you can try breaking it yourself and see where traditional controls fail.

Happy to discuss the technical details, threat model, and mitigations in the comments.
sandeep_kamble
·昨年·議論
Congratulations Paras, you made it! Looking forward to your next gig!