Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

On August 13, security researchers at Tel Aviv University disclosed a new HTTP/2 denial-of-service (DoS) vulnerability that they are calling MadeYouReset (CVE-2025-8671). This vulnerability exists in a limited number of unpatched HTTP/2 server implementations that do not sufficiently enforce restrictions on the number of times a client may send malformed frames. If you’re using Cloudflare for HTTP DDoS mitigation, you’re already protected from MadeYouReset.

CVE-2025-53770 and CVE-2025-53771 are critical remote code execution vulnerabilities (CVSS base score 9.8) impacting Microsoft SharePoint, a widely deployed enterprise collaboration and content management platform. In this blog, we will simulate the exploitation of this SharePoint RCE vulnerability and analyze the resulting telemetry inside Graylog.

The question isn’t whether security information and event management (SIEM) is dead. The real question is whether the traditional model of SIEM still serves today’s defenders. Spoiler alert: it doesn’t. Born from compliance needs and static rules, first-generation SIEMs provided log collection and correlation but not context. They buried analysts in noise and left threat detection slow, brittle, and expensive. But that’s changing.

The importance of a cybersecurity vendor being Federal Risk and Authorization Management Program (FedRAMP) authorized cannot be understated. In February 2025, after a multi-year process, Trustwave achieved full FedRAMP authorization for its Government Fusion platform, becoming the first pure-play Managed Detection and Response (MDR) provider to do so.

As security researchers, we actively monitor the latest CVEs and their publicly available exploits to create signatures. Beyond CVEs, we also hunt for malware on platforms such as MalwareBazaar, which enhances our visibility into attacks occurring across networks. Today, we'll demonstrate a simple workflow showing how researchers use various tools to collect indicators of compromise (IOCs) and develop appropriate signatures from detonated malware.

IBM’s 2025 Cost of a Data Breach Report offers one of the clearest and most comprehensive views yet of how AI adoption is shaping the security landscape. While breach numbers are relatively low – only 13% of organizations reported breaches involving AI models or applications – the report reveals a troubling pattern: APIs and integrations are often the real entry point, and they’re frequently under-secured. At Wallarm, we’ve been banging this drum for a while.

Organizations are under constant threat from vulnerabilities hidden deep within their own systems and applications. Uncovering these types of weaknesses before they lead to security issues such as malware, ransomware attacks and social engineering is a challenge that Jugal Bhatt and Jonathan Hosick take on every day.

On June 23, 2025, the Federal Trade Commission’s sweeping amendments to the Children’s Online Privacy Protection Rule (COPPA) took effect, ushering in more stringent duties for any operator collecting or using children’s data—whether via websites, services, or AI‑powered agents. Companies must achieve full compliance by April 22, 2026 (Finnegan | Leading IP+ Law Firm, Bass, Berry & Sims PLC).

Imagine an autonomous AI agent tasked with a simple job: generating a weekly sales report. It does this reliably every Monday. But one week, it doesn't just create the report. It also queries the customer database, exports every single record, and sends the file to an unknown external server. Your firewalls saw nothing wrong. Your API gateway logged a series of seemingly valid calls. So, what happened? The agent wasn't hacked. Its mind was changed.

Model Context Protocol (MCP) is gaining traction because it enables LLMs to interact with live systems and enhance context by retrieving and managing relevant real-time information. LLMs can’t query Salesforce, trigger an Okta password reset, or fetch context from your SIEM, for example. MCP bridges that gap by connecting AI models to real-world APIs, powering AI applications like retrieval-augmented generation and multi-step agent workflows. They’re fast to deploy.