Threat actors are advancing AI strategies and outpacing traditional security. CXOs must critically examine AI weaponization across the attack chain.
The integration of AI into adversarial operations is fundamentally reshaping the speed, scale and sophistication of attacks. As AI defense capabilities evolve, so do the AI strategies and tools leveraged by threat actors, creating a rapidly shifting threat landscape that outpaces traditional detection and response methods. This accelerating evolution necessitates a critical examination for CXOs into how threat actors will strategically weaponize AI across each phase of the attack chain.
One of the most alarming shifts we have seen, following the introduction of AI technologies, is the dramatic drop in mean time to exfiltrate (MTTE) data, following initial access. In 2021, the average MTTE stood at nine days. According to our Unit 42 2025 Global Incident Response Report, by 2024 MTTE dropped to two days. In one in five cases, the time from compromise to exfiltration was less than 1 hour.
In our testing, Unit 42 was able to simulate a ransomware attack (from initial compromise to data exfiltration) in just 25 minutes using AI at every stage of the attack chain. That’s a 100x increase in speed, powered entirely by AI.
Recent threat activity observed by Unit 42 has highlighted how adversaries are leveraging AI in attacks:
Discover how to intercept data stolen by cybercriminals via Telegram bots and learn to use it to clarify related threat landscape.
While analyzing malware samples uploaded to ANY.RUN’s Interactive Sandbox, one particular case marked as “phishing” and “Telegram” drew the attention of our security analysts.
Although this analysis session wasn’t attributed to any known malware family or threat actor group, the analysis revealed that Telegram bots were being used for data exfiltration. This led us to apply a message interception technique for Telegram bots, previously described on the ANY.RUN blog.
The investigation resulted in a clear and practical case study demonstrating how intercepting Telegram bot communications can aid in profiling the threat actor behind a relatively obscure phishing campaign.
Key outcomes of this analysis include:
Examination and technical analysis of a lesser known phishing campaign
Demonstration of Telegram API-based data interception techniques
Collection of threat intelligence (TI) indicators to help identify the actor
Recommendations for detecting this type of threat
Berne, 29.04.2025 — Pour la première fois, le commandement Cyber publie le code source d’un logiciel qu’il a lui-même développé, appelé « Loom ». Celui-ci permet de créer un recueil rapidement consultable à partir de vastes séries de données et de divers types de fichiers. Le Groupement Défense fait ainsi une avancée significative vers plus de transparence et de collaboration.
Pour la première fois, le commandement Cyber permet au public d’accéder, à travers GitLab, à une plate-forme performante de recherche et d’analyse. Il s’agit du logiciel « Loom ». Un de ses avantages importants est sa souplesse : son code source étant public, des organisations peuvent adapter ce logiciel à leurs propres besoins. De nouvelles fonctions peuvent y être intégrées, d’où la possibilité de l’utiliser pour des applications spécifiques.
« Loom » permet de réaliser efficacement et aisément des recherches parmi un très grand nombre de données. Il gère une multitude de types de fichiers et offre rapidement aux utilisateurs une vue d’ensemble d’un jeu de données. Il les aide à s’y plonger pour obtenir des résultats plus précis au lieu de se limiter à parcourir superficiellement une grande quantité de données.
KrebsOnSecurity last week was hit by a near record distributed denial-of-service (DDoS) attack that clocked in at more than 6.3 terabits of data per second (a terabit is one trillion bits of data). The brief attack appears to have been…
For reference, the 6.3 Tbps attack last week was ten times the size of the assault launched against this site in 2016 by the Mirai IoT botnet, which held KrebsOnSecurity offline for nearly four days. The 2016 assault was so large that Akamai – which was providing pro-bono DDoS protection for KrebsOnSecurity at the time — asked me to leave their service because the attack was causing problems for their paying customers.
Since the Mirai attack, KrebsOnSecurity.com has been behind the protection of Project Shield, a free DDoS defense service that Google provides to websites offering news, human rights, and election-related content. Google Security Engineer Damian Menscher told KrebsOnSecurity the May 12 attack was the largest Google has ever handled. In terms of sheer size, it is second only to a very similar attack that Cloudflare mitigated and wrote about in April.
After comparing notes with Cloudflare, Menscher said the botnet that launched both attacks bears the fingerprints of Aisuru, a digital siege machine that first surfaced less than a year ago. Menscher said the attack on KrebsOnSecurity lasted less than a minute, hurling large UDP data packets at random ports at a rate of approximately 585 million data packets per second.
“It was the type of attack normally designed to overwhelm network links,” Menscher said, referring to the throughput connections between and among various Internet service providers (ISPs). “For most companies, this size of attack would kill them.”
