Military forces are under increasing pressure to field autonomous capabilities faster than ever before. Across the U.S., UK, and NATO, new investment, evolving defense strategies, and accelerated acquisition pathways are transforming how capability is delivered, rewarding programs that can move from concept to operational deployment at commercial speed.
Now the focus shifts to the trusted
More than 20 Brazilian government websites were hijacked and turned into malware delivery channels in an active PhantomEnigma campaign uncovered by ANY.RUN, a leading provider of interactive malware analysis and threat intelligence solutions.
The investigation revealed previously undocumented backdoor behavior, hidden infrastructure relationships, and multiple attack arms behind a campaign
Artificial intelligence (AI) is changing offensive security, but it has not changed the standard that matters most: a finding has to be proven before it becomes useful. AI-assisted tools can read code quickly, generate payloads, summarize attack surfaces, explain unfamiliar APIs, and run repetitive testing workflows at impressive speed. That is a real advantage for security teams. It also
AI security agents are starting to influence real security decisions. They summarize findings, prioritize remediation, recommend next steps, and help teams move faster. But most still rely on fragmented risk signals: scanner output, severity scores, threat intelligence, configuration findings, and exposure data.
That fragmentation matters because attackers do not move through environments one
A few days ago, I was sitting with the CISO of a Fortune 50 company, walking through how his security team was thinking about AI agents in the SOC. Smart team. Serious program. They had already connected Claude to a few detection tools and were seeing real value in specific investigations. But as we mapped out the broader architecture, something kept nagging at me. The design they were building
Most enterprises assume their asset inventory is close enough to accurate. The evidence suggests otherwise. According to a survey of over 600 security leaders in the 2026 Axonius Actionability Report, only 45% of organizations consolidate their asset and exposure data into a single view, and every downstream security program inherits whatever the inventory gets wrong.
Lumen Technologies, a
AI has changed how fast attacks move. Work that once took an attacker days now takes minutes. Using models like Mythos, attackers write tailored bait, pick targets, test what lands, and jump to the next host before your team clears the first alert.
That is the gap, and it is not your fault. The tools and runbooks most teams run on were built for attackers who work at human speed. AI-driven
Everyone seems to have announced a clearinghouse over the past few weeks. We did too. Ours is called Athena, and the main thing that sets it apart is that it was already real and running when we announced it β built quietly months earlier, heads down, taking findings and shipping fixes, because customers kept asking us to. We only announced it now because everyone else started announcing theirs,
A recent EvilTokens campaign targeting businesses across the US and Europe is exposing a new email security blind spot. This βghost phishingβ technique keeps the malicious page hidden until it decrypts and comes to life inside the victimβs browser.
For security leaders, the risk is clear: traditional URL checks may miss the attack while Microsoft 365 access, sensitive data, and response time
For years, account takeover (ATO) followed a predictable script. Attackers bought stolen credentials in bulk, ran them through automated tools, and waited for matches. Credential stuffing was cheap, scalable, and for defenders, relatively well understood.
That era is ending. Not because attackers gave up, but because the front door finally got harder to kick in.
Passkeys are now mainstream.
Software supply chain security was hard enough. Then AI joined the build pipeline.
For five years, "software supply chain security" meant one question: what's in your code? Which open-source packages, which versions, which transitive dependencies three layers deep that nobody chose on purpose?
SolarWinds, Log4Shell, and XZ Utils all taught the same lesson: the risk lives less in the code a