What we learned mapping a year’s worth of AI-enabled cyber threats
Anthropic released a new report examining 832 banned accounts for malicious cyber activity between March 2025 and March 2026. The study maps these AI-enabled threats onto the MITRE ATT&CK framework and details how attackers are shifting from initial access to post-compromise tasks.
The Core Development
As AI transforms the nature of and methods behind cyberattacks, how well do the techniques and frameworks used by the security community hold up?
In a new report, we seek to answer that question. We examine 832 accounts that were banned for malicious cyber activity between March 2025 and March 2026 and map them onto MITRE ATT&CK , a longstanding database of the tactics and techniques used by cyberattackers. We published some of these results in Verizon’s 2026 Data Breach Investigations Report (DBIR), and are sharing a more detailed analysis here. These 832 cases are just a subset of the total number of accounts banned during this period, but they represent those where we had enough detail to conduct a thorough assessment of the attackers’ techniques.
Below we provide a summary of each of these conclusions. You can read a longer analysis on our Frontier Red Team blog .
Strategic Perspective & Ecosystem Impact
The most common AI-enabled activities in our database related to preparing for a cyberattack, such as writing malware (560 of the 832 accounts we studied, or 67.3%, used AI for this purpose). A smaller number of actors use AI for more complex activities—for example, 54 of the 832 actors (6.5%) used AI to assist with “lateral movement,” which involves navigating deep inside a compromised network.
We found evidence consistent with AI being used to help increase the threat level of attackers. In the first six-month period of our analysis, 33% of actors were classified by our risk-scoring system as medium risk or higher. But by the second six-month period, that share had jumped to 56%—a roughly 1.7-fold increase.
Across the period we studied, attackers’ use of AI shifted from techniques to gain initial access to a system towards activity carried out once they were inside the system. For example, the use of AI for account discovery—identifying valid accounts inside a compromised environment—rose 8.9%, while AI-assisted phishing—a common technique to gain access to a system—fell 8.6%. This suggests that attackers are increasingly applying AI deeper in the attack life cycle.
Why it matters
The findings highlight that traditional metrics like technique counts no longer accurately measure cyber risk, pointing to an urgent need for security frameworks to adapt to autonomous, agentic AI attacks.