The CISO Playbook for AI Agents | Datadog
The discussion centers on the risks and opportunities presented by AI in cybersecurity, with an emphasis on understanding and managing malicious intent in code. Datadog's CISO, Emilio Escobar, highlights the importance of proactive security measures, including using AI to evaluate code intent and assessing new AI tools rather than outright blocking them.
Summary
In this episode, Emilio Escobar, CISO of Datadog, elaborates on the current state of AI in cybersecurity and the potential threats posed by AI agents. He expresses concern over what these agents can do in terms of accessing tools, binaries, and credentials. Escobar emphasizes the need for organizations to adopt AI technologies while being vigilant about security. He reflects on the evolution of internal practices at Datadog, which began with small-scale AI adoption and grew to almost universal usage among employees. Escobar argues against the traditional approach of blocking new tools, noting that allowing employees to use these tools can prevent important security oversights.
He discusses the measures taken to safeguard against malicious code, including a tool created by his team, referred to as a 'judge', which evaluates the intent behind code contributions. Escobar points out that the landscape of vulnerabilities could drastically increase as AI becomes more adept at identifying them, raising concerns about how to manage and address this influx. He calls for a shift in security practices that acknowledges the realities of a rapidly evolving technological landscape rather than relying solely on traditional methods. Ultimately, Escobar's insights reflect a balancing act between leveraging AI capabilities and maintaining robust security measures.
About this episode
a16z's Joel De La Garza is joined by Emilio Escobar, Chief Information Security Officer at Datadog, to discuss what it takes to secure a company where nearly every employee is using AI and more than 4,000 engineers are working with coding agents. Rather than trying to block new tools, Emilio explains why Datadog chose to embrace AI early and build the security infrastructure needed to use it safely. They unpack how AI changes traditional assumptions around data permissions, credentials, developer access, and software supply chains. Emilio shares how Datadog uses role-based MCP servers and ephemeral credentials, as well as an AI "judge" built by his security team to evaluate the intent behind code and agent skills before they enter the environment. They also discuss why security teams can't afford to wait for commercial solutions to every new AI threat, how the relationship between developers and security teams needs to change, and why Emilio is less concerned about an AI "escaping" than he is about the sheer volume of vulnerabilities AI could uncover.
Key Insights
- Emilio Escobar emphasizes that while AI tools can enhance security responses, they also present new risks, particularly regarding credential access and malicious intent in code.
- He argues that traditional methods of blocking new tools are ineffective and promotes a strategy of enabling employees to use AI technologies while ensuring they are safe.
- Escobar highlights the role of his team's 'judge' tool, which evaluates the intent behind code to help identify malicious contributions and improve security measures.
- He expresses concern that advancements in AI could lead to a massive increase in the number of vulnerabilities that need to be managed by security teams.
- Escobar suggests that the security profession is undergoing a shift where the lines between development and security are blurring, pushing for a more integrated approach to these disciplines.
Topics
Transcript
The number one story on Bloomberg right now is that AI has gone wild. We seem remarkably calm. The way I see it is, if it's not an AI model, it's going to be somebody or something with actual malicious intent doing it. I do worry about what can the agents do, what tools can they call, what binaries can they pull, and also how do they get access to credentials. If a code is meant to solve the bug but it gets rewarded on that, but it doesn't care if it's actually doing something else. The tree is sick, so to make it healthy, it cuts it down. Out of necessity, my team built a judge that evaluates the…
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