Safeguarding Against Malicious Use of Large Language Models: A Review of the OWASP Top 10 for LLMs
0Guest: Jason Haddix, CISO and Hacker in Charge at BuddoBot Inc [@BuddoBot]
On LinkedIn | https://www.linkedin.com/in/jhaddix/
On Twitter | https://twitter.com/Jhaddix
Host: Sean Martin, Co-Founder at ITSPmagazine [@ITSPmagazine] and Host of Redefining CyberSecurity Podcast [@RedefiningCyber]
On ITSPmagazine | https://www.itspmagazine.com/itspmagazine-podcast-radio-hosts/sean-martin
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This Episodeβs Sponsors
Imperva | https://itspm.ag/imperva277117988
Pentera |Β https://itspm.ag/penteri67a
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In this Redefining CyberSecurity Podcast, we provide an in-depth exploration of the potential implications of large language models (LLMs) and artificial intelligence in the cybersecurity landscape. Jason Haddix, a renowned expert in offensive security, shares his perspective on the evolving risks and opportunities that these new technologies bring to businesses and individuals alike. Sean and Jason explore the potential risks of using LLMs:
π Prompt Injections
π§ Data Leakage
ποΈ Inadequate Sandboxing
π Unauthorized Code Execution
π SSRF Vulnerabilities
βοΈ Overreliance on LLM-generated Content
π§ Inadequate AI Alignment
π« Insufficient Access Controls
β οΈ Improper Error Handling
π Training Data Poisoning
From the standpoint of offensive security, Haddix emphasizes the potential for LLMs to create an entirely new world of capabilities, even for non-expert users. He envisages a near future where AI, trained on diverse datasets like OCR and image recognition data, can answer private queries about individuals based on their public social media activity. This potential, however, isn't limited to individuals - businesses are equally at risk.
According to Haddix, businesses worldwide are rushing to leverage proprietary data they've collected in order to generate profits. They envision using LLMs, such as GPT, to ask intelligent questions of their data that could inform decisions and fuel growth. This has given rise to the development of numerous APIs, many of which are integrated with LLMs to produce their output.
However, Haddix warns of the vulnerabilities this widespread use of LLMs might present. With each integration and layer of connectivity, opportunities for prompt injection attacks increase, with attackers aiming to exploit these interfaces to steal data. He also points out that the very data a company uses to train its LLM might be subject to theft, with hackers potentially able to smuggle out sensitive data through natural language interactions.
Another concern Haddix raises is the interconnected nature of these systems, as companies link their LLMs to applications like Slack and Salesforce. The connections intended for data ingestion or query could also be exploited for nefarious ends. Data leakage, a potential issue when implementing LLMs, opens multiple avenues for attacks.
Sean Martin, the podcast's host, echoes Haddix's concerns, imagining scenarios where private data could be leveraged and manipulated. He notes that even benign-seeming interactions, such as conversing with a bot on a site like Etsy about jacket preferences, could potentially expose a wealth of private data.
Haddix also warns of the potential to game these systems, using the Etsy example to illustrate potential data extraction, including earnings of sellers or even their private location information. He likens the data leakage possibilities in the world of LLMs to the potential dangers of SQL injection in the web world. In conclusion, Haddix emphasizes the need to understand and safeguard against these risks, lest organizations inadvertently expose themselves to attack via their own LLMs.
All OWASP Top 10 items are reviewed, along with a few other valuable resources (listed below).
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Resources
Redefining CyberSecurity Podcast with Sean Martin, CISSP playlist:
πΊ https://www.youtube.com/playlist?list=PLnYu0psdcllQZ9kSG7X7grrP_PsH3q3T3ITSPmagazine YouTube Channel:
πΊ https://www.youtube.com/@itspmagazine
The inspiring Tweet: https://twitter.com/Jhaddix/status/1661477215194816513
OWASP Top 10 List for Large Language Models Descriptions: https://owasp.org/www-project-top-10-for-large-language-model-applications/descriptions/
Daniel Miessler Blog: The AI attack Surface Map 1.0: https://danielmiessler.com/p/the-ai-attack-surface-map-v1-0/
Gandalf AI Playground: https://gandalf.lakera.ai/
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