Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

When it comes to choosing a manufacturer to target for attack, threat groups have a healthy list of tools from which to choose. All of which are made more powerful due to this industry’s complex cybersecurity posture, driven by the increasing integration of IT/OT environments.

Ransomware attacks have emerged as a significant threat to educational institutions. Cybercriminals encrypt sensitive data and demand payment for its release, severely disrupting school operations and leading to exorbitant recovery costs for districts. With ransomware tactics continually evolving, the security of the entire U.S. education system is at risk.

ByBit’s recent attack has exposed a critical flaw in how many exchanges approach security. The real-time transaction manipulation that took place wasn’t just an unfortunate event—it was a direct consequence of mispurposed security architectures that sophisticated attackers are all too ready to exploit.

Are you still running your package pipeline on default settings and grabbing libraries straight from public repos? Big yikes. That’s rolling out the red carpet for dependency confusion attacks to drop shady code into your project. It isn’t uncommon. Nearly half (49%) of organizations are exposed to the risks of a dependency confusion attack because they make the same mistakes. But what exactly is dependency confusion, and how do these attacks manage to infiltrate?

As the adage goes, time is money, and nowhere does this ring more true than in an evolving threat landscape. The faster companies detect, respond, and recover from data breaches, the better for their pockets. Using AI and security automation to shorten the breach lifecycle has been shown to save $2.2 million more on average compared to not employing these technologies.

In today’s threat landscape, detecting and responding to distributed attacks is more challenging than ever. Attackers often operate in stealth, using coordinated strategies to blend into normal traffic and evade detection. To address this issue, Datadog Application Security Management (ASM) has a new clustering feature designed to identify and group attacker behaviors during distributed attacks.

We already know that cybercriminals exploit the weakest link in your IT networks. The best defense against these exploits comes down to safeguarding the most vulnerable entry points. But what if the weakest link in your cybersecurity defense lies beyond your IT network itself?

In the first part of Trustwave SpiderLabs’ Russia-Ukraine war blog series, we gave a brief look at our major findings as well as the main differences between how Russia and Ukraine wage attacks in the digital frontlines. In this part of our series, we shed light on how both countries target government entities, defense organizations, and even human targets as part of their overall strategy to win the war.

The cybersecurity industry is facing a new challenge: AI-generated attacks. With the rapid advancement of generative AI, cybercriminals now have access to sophisticated tools that enable them to craft highly targeted attacks with minimal technical expertise. Unlike traditional attack methods that require deep programming knowledge, AI-driven attacks allow even non-technical malicious actors to create malware, exploit scripts, and launch phishing campaigns with ease.