AI Threat Intelligence

Unless you’ve been living off the grid for the past decade, you know what artificial intelligence (AI) is. What about AI in the world of threat intelligence?

What is AI Threat Intelligence?

AI in threat intelligence refers to the use of artificial intelligence technologies and techniques to improve the detection, analysis, and response to cyber threats. AI threat intelligence automates the process of collecting and analyzing information about threat actor behaviors and vulnerabilities across the clear and dark web.

Ultimately, its power is in the beholder: AI can be used for threat hunting and accelerated threat response, but it can also be used maliciously in ways not seen before, like WormGPT.

The threat intel world before AI 

While AI is a relatively new arrival to the threat intelligence space, the threat landscape has been increasingly digital for several years now. Not only that, but those cyber threats are converging, with data breaches, information-stealing malware, vulnerabilities, and ransomware taking center stage. 

Tracking those threats was difficult, requiring teams to wade through overwhelming amounts of data and tune out noisy, often irrelevant alerts. 

AI Threats: Infostealers, Malicious GPTs, Phishing, Deepfakes, and more

As if threat intelligence and threat hunting weren’t difficult enough, artificial intelligence introduced new challenges.

What are examples of AI-driven cyber threats?  

• Deepfake-enabled fraud: AI is used to create highly realistic synthetic media for deceptive purposes, for use in cyberattacks and scams.
• Jailbroken LLMs: These are Large Language Models that have been intentionally manipulated to bypass safety and ethical guidelines.
• Multilingual phishing campaigns: Phishing attacks designed and executed across multiple languages, making them more effective against diverse global targets.
• Voice-cloning services: Using AI, highly realistic synthetic voices are created to mimic an individual, being highly effective in phishing and social engineering attacks.
• Prompt-injection attacks: attackers manipulate an AI or Large Language Model (LLM) by providing cleverly crafted input (prompts) to make it behave in ways it was not intended to, often overriding its safety guidelines or performing actions beneficial to the attacker.

With infostealers, attackers often use AI to rapidly parse, prioritize, and monetize the immense volume of stolen credentials and data logs, allowing threat actors to identify high-value targets (like financial accounts or corporate VPN access) at scale and unprecedented speed.

Like all AI algorithms, the ones used by AI-powered cyberattacks can learn and evolve over time. This means that AI-enabled cyberattacks can adapt to avoid detection or create a pattern of attack that a security system can’t detect.

However, artificial intelligence has also helped fortify network security, anti-malware, and fraud detection efforts by reducing the burden on security teams.

Like all AI algorithms, the ones used by AI-powered cyberattacks can learn and evolve over time. This means that AI-enabled cyberattacks can adapt to avoid detection or create a pattern of attack that a security system can’t detect.

However, artificial intelligence has also helped fortify network security, anti-malware, and fraud detection efforts by reducing the burden on security teams. 

AI Threat Detection

How can AI help security teams with threat detection? 

AI can help security teams match adversaries by automating triage and extending analyst research. 

• Threat hunting: Spotting indicators of compromise (IoCs) in large data
• Data analysis: Leverage AI’s strength in pattern recognition to identify patterns in an organization’s security data
• Scanning: AI tools can perform scans all hours of the day, enabling teams to proactively catch instances of “brandjacking”, data leakage, or other external threats like malware, hacking, and social engineering attacks

AI Phishing Detection with Threat Intelligence​

AI phishing detection is the modern, automated defense against increasingly sophisticated and personalized phishing attacks where AI models are used to generate hidden scripts and other harmful code. Defenders are leveraging AI to analyze context, behavior, and emerging global threats in real time. 

AI detects what traditional filters miss by focusing on behavior (“is this writing style common for executives?”) and structural anomalies (such as a URL that is technically disguised or code that looks “formulaic” or machine-generated).

💡 AI and Flashpoint CTI can work together to detect and block phishing campaigns before they reach users. With CTI analyzing the external threat landscape and AI analyzing the content of messages, defenders can flag and eliminate threats early.

What to look for in an AI threat intelligence solution?

If your organization is looking into AI threat intelligence solutions, the following factors are crucial to consider:

• Data quality: More is not always better. Excess noise can cause actual threats to go unnoticed. Look for a threat intelligence provider that sends specific, relevant alerts, rather than a “shotgun” approach.
• Data sources: Most intelligence vendors collect from the same set of publicly available sources, apply a few layers of enrichment, and then offer pre-packaged access to the same feed of generalized data. Look for an intelligence provider that offers primary source intelligence (closed forums, private messaging channels, fringe platforms, etc).
• Integrations: The ideal intelligence solution provides data where you are, combining seamlessly with your existing tech stack, such as SIEMs and ticketing technologies. Look for a threat intelligence provider that helps you do more with the tools you have.

Flashpoint’s AI Philosophy

What is the future of AI in threat intelligence? 

Our belief is that AI is a force multiplier for threat analysts, not a replacement. It can’t substitute for the sharp minds, context, and judgment of our analysts or the critical expertise of our customers. Rather, it’s here to help them do more, with greater clarity and confidence. 

AI today excels at pattern detection, rapid triage, and large-scale summarization. This pairs very well with the tradecraft, experience, and full-context understanding that only human analysts bring. 

The Power of Flashpoint’s AI: Specific Features and Use Cases

What are the key benefits of Flashpoint’s AI threat intelligence solution?

Flashpoint applies AI strategically, grounding our approach in analyst workflows and customer outcomes. Check out the latest from Flashpoint’s AI offerings here.

How does Flashpoint’s AI threat intelligence compare to other threat intelligence platforms like Flare or Recorded Future?

Flashpoint offers a unique combination of AI-powered intelligence along with finished intelligence generated by expert analysts who bring years of irreplaceable experience. No other threat intelligence platform offers that. Flashpoint also offers primary source collection, rather than relying on data sourced from other providers.

What changes has Flashpoint seen with AI in the threat intelligence lifecycle?

The Flashpoint team has been keeping a close eye on the use of AI in the threat intelligence lifecycle, and we’ve collected intelligence and survey results to publish AI and Threat Intelligence: The Defenders’ Guide.

Powering This Analysis:

• 2.6M+ AI-related posts analyzed across underground sources in just five months—including jailbreak prompts, fraud toolkits, and deepfake services
• 100,000+ illicit sources tracked, giving unmatched visibility into how adversaries are experimenting, optimizing, and operationalizing AI
• 5 distinct threat actor use cases, from multilingual phishing kits to synthetic voice impersonation tools