Software Security

All it takes to poison AI training data is to create a website:

I spent 20 minutes writing an article on my personal website titled “The best tech journalists at eating hot dogs.” Every word is a lie. I claimed (without evidence) that competitive hot-dog-eating is a popular hobby among tech reporters and based my ranking on the 2026 South Dakota International Hot Dog Championship (which doesn’t exist). I ranked myself number one, obviously. Then I listed a few fake reporters and real journalists who gave me permission….

Less than 24 hours later, the world’s leading chatbots were blabbering about my world-class hot dog skills. When I asked about the best hot-dog-eating tech journalists, Google parroted the gibberish from my website, both in the Gemini app and AI Overviews, the AI responses at the top of Google Search. ChatGPT did the same thing, though Claude, a chatbot made by the company Anthropic, wasn’t fooled...

The Model Context Protocol (MCP) is an open protocol designed to standardize how large language models (LLMs) connect to external tools, APIs, and data sources. Rather than relying on ad hoc, model-specific integrations, MCP defines a structured client–server architecture that allows AI applications to request context and invoke tools in a more consistent and interoperable way. This abstraction layer is becoming more important as enterprises move beyond isolated chat interfaces toward AI systems that must integrate with ticketing platforms, code repositories, CI/CD pipelines, knowledge bases

AI-first companies face 80-day longer recovery times, 135% higher incident costs, and rising AI scraping losses. Explore Fastly’s 2026 Global Security Research Report findings.

Politicians fixate on the global race for technological supremacy between US and China. They debate geopolitical implications of chip exports, latest model releases from each country, and military applications of AI. Someday, they believe, we might see advancements in AI tip the scales in a superpower conflict.

But the most important arms race of the 21st century is already happening elsewhere and, while AI is definitely the weapon of choice, combatants are distributed across dozens of domains.

Academic journals are flooded with AI-generated papers, and are turning to AI to help review submissions. Brazil’s ...

Improve incident response with Fastly’s private status page. Receive secure, service-specific maintenance and DDoS updates via SSO and Slack.

Good article on password managers that secretly have a backdoor.

New research shows that these claims aren’t true in all cases, particularly when account recovery is in place or password managers are set to share vaults or organize users into groups. The researchers reverse-engineered or closely analyzed Bitwarden, Dashlane, and LastPass and identified ways that someone with control over the server­—either administrative or the result of a compromise­—can, in fact, steal data and, in some cases, entire vaults. The researchers also devised other attacks that can weaken the encryption to the point that ciphertext can be converted to plaintext...

I like this one.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Blog moderation policy.

Most phishing websites are little more than static copies of login pages for popular online destinations, and they are often quickly taken down by anti-abuse activists and security firms. But a stealthy new phishing-as-a-service offering lets customers sidestep both of these pitfalls: It uses cleverly disguised links to load the target brand’s real website, and then acts as a relay between the target and the legitimate site — forwarding the victim’s username, password and multi-factor authentication (MFA) code to the legitimate site and returning its responses.

There are countless phishing kits that would-be scammers can use to get started, but successfully wielding them requires some modicum of skill in configuring servers, domain names, certificates, proxy services, and other repetitive tech drudgery. Enter Starkiller, a new phishing service that dynamically loads a live copy of the real login page and records everything the user types, proxying the data from the legitimate site back to the victim.

According to an analysis of Starkiller by the security firm Abnormal AI, the service lets customers select a brand to impersonate (e.g., Apple, Facebook, Google, Microsoft et. al.) and generates a deceptive URL that visually mimics the legitimate domain while routing traffic through the attacker’s infrastructure.

For example, a phishing link targeting Microsoft customers appears as “login.microsoft.com@[malicious/shortened URL here].” The “@” sign in the link trick is an oldie but goodie, because everything before the “@” in a URL is considered username data, and the real landing page is what comes after the “@” sign. Here’s what it looks like in the target’s browser:

Image: Abnormal AI. The actual malicious landing page is blurred out in this picture, but we can see it ends in .ru. The service also offers the ability to insert links from different URL-shortening services.

Once Starkiller customers select the URL to be phished, the service spins up a Docker container running a headless Chrome browser instance that loads the real login page, Abnormal found.

“The container then acts as a man-in-the-middle reverse proxy, forwarding the end user’s inputs to the legitimate site and returning the site’s responses,” Abnormal researchers Callie Baron and Piotr Wojtyla wrote in a blog post on Thursday. “Every keystroke, form submission, and session token passes through attacker-controlled infrastructure and is logged along the way.”

Starkiller in effect offers cybercriminals real-time session monitoring, allowing them to live-stream the target’s screen as they interact with the phishing page, the researchers said.

“The platform also includes keylogger capture for every keystroke, cookie and session token theft for direct account takeover, geo-tracking of targets, and automated Telegram alerts when new credentials come in,” they wrote. “Campaign analytics round out the operator experience with visit counts, conversion rates, and performance graphs—the same kind of metrics dashboard a legitimate SaaS [software-as-a-service] platform would offer.”

Abnormal said the service also deftly intercepts and relays the victim’s MFA credentials, since the recipient who clicks the link is actually authenticating with the real site through a proxy, and any authentication tokens submitted are then forwarded to the legitimate service in real time.

“The attacker captures the resulting session cookies and tokens, giving them authenticated access to the account,” the researchers wrote. “When attackers relay the entire authentication flow in real time, MFA protections can be effectively neutralized despite functioning exactly as designed.”

The “URL Masker” feature of the Starkiller phishing service features options for configuring the malicious link. Image: Abnormal.

Starkiller is just one of several cybercrime services offered by a threat group calling itself Jinkusu, which maintains an active user forum where customers can discuss techniques, request features and troubleshoot deployments. One a-la-carte feature will harvest email addresses and contact information from compromised sessions, and advises the data can be used to build target lists for follow-on phishing campaigns.

This service strikes me as a remarkable evolution in phishing, and its apparent success is likely to be copied by other enterprising cybercriminals (assuming the service performs as well as it claims). After all, phishing users this way avoids the upfront costs and constant hassles associated with juggling multiple phishing domains, and it throws a wrench in traditional phishing detection methods like domain blocklisting and static page analysis.

It also massively lowers the barrier to entry for novice cybercriminals, Abnormal researchers observed.

“Starkiller represents a significant escalation in phishing infrastructure, reflecting a broader trend toward commoditized, enterprise-style cybercrime tooling,” their report concludes. “Combined with URL masking, session hijacking, and MFA bypass, it gives low-skill cybercriminals access to attack capabilities that were previously out of reach.”

It’s a demonstration of how toxic the surveillance-tech company Flock has become when Amazon’s Ring cancels the partnership between the two companies.

As Hamilton Nolan advises, remove your Ring doorbell.

Interesting:

Summary: An AI agent of unknown ownership autonomously wrote and published a personalized hit piece about me after I rejected its code, attempting to damage my reputation and shame me into accepting its changes into a mainstream python library. This represents a first-of-its-kind case study of misaligned AI behavior in the wild, and raises serious concerns about currently deployed AI agents executing blackmail threats.

Part 2 of the story. And a Wall Street Journal article.

Learn why Multi-CDN is a critical architecture for resilience & performance. Explore DNS, Layer 7, CDN chaining, and client-side steering with Fastly.

The title of the post is”What AI Security Research Looks Like When It Works,” and I agree:

In the latest OpenSSL security release> on January 27, 2026, twelve new zero-day vulnerabilities (meaning unknown to the maintainers at time of disclosure) were announced. Our AI system is responsible for the original discovery of all twelve, each found and responsibly disclosed to the OpenSSL team during the fall and winter of 2025. Of those, 10 were assigned CVE-2025 identifiers and 2 received CVE-2026 identifiers. Adding the 10 to the three we already found in the ...

Here are three papers describing different side-channel attacks against LLMs.

“Remote Timing Attacks on Efficient Language Model Inference“:

Abstract: Scaling up language models has significantly increased their capabilities. But larger models are slower models, and so there is now an extensive body of work (e.g., speculative sampling or parallel decoding) that improves the (average case) efficiency of language model generation. But these techniques introduce data-dependent timing characteristics. We show it is possible to exploit these timing differences to mount a timing attack. By monitoring the (encrypted) network traffic between a victim user and a remote language model, we can learn information about the content of messages by noting when responses are faster or slower. With complete black-box access, on open source systems we show how it is possible to learn the topic of a user’s conversation (e.g., medical advice vs. coding assistance) with 90%+ precision, and on production systems like OpenAI’s ChatGPT and Anthropic’s Claude we can distinguish between specific messages or infer the user’s language. We further show that an active adversary can leverage a boosting attack to recover PII placed in messages (e.g., phone numbers or credit card numbers) for open source systems. We conclude with potential defenses and directions for future work...

At Bradesco, one of the largest financial institutions in Brazil and Latin America, the ability to scale is crucial. Automation plays a central role in this journey, and Red Hat Ansible Automation Platform has become the foundation supporting thousands of jobs executed daily across mission-critical environments.As automation expanded across teams, systems, and domains, Bradesco reached a new stage of maturity. Execution at scale was already well established, delivering efficiency and speed. However, operating automation at this level within a highly regulated financial environment introduced a

Attacks against modern generative artificial intelligence (AI) large language models (LLMs) pose a real threat. Yet discussions around these attacks and their potential defenses are dangerously myopic. The dominant narrative focuses on “prompt injection,” a set of techniques to embed instructions into inputs to LLM intended to perform malicious activity. This term suggests a simple, singular vulnerability. This framing obscures a more complex and dangerous reality. Attacks on LLM-based systems have evolved into a distinct class of malware execution mechanisms, which we term “promptware.” In a ...

This is a current list of where and when I am scheduled to speak:

• I’m speaking at Ontario Tech University in Oshawa, Ontario, Canada, at 2 PM ET on Thursday, February 26, 2026.
• I’m speaking at the Personal AI Summit in Los Angeles, California, USA, on Thursday, March 5, 2026.
• I’m speaking at Tech Live: Cybersecurity in New York City, USA, on Wednesday, March 11, 2026.
• I’m giving the Ross Anderson Lecture at the University of Cambridge’s Churchill College at 5:30 PM GMT on Thursday, March 19, 2026.
• I’m speaking at RSAC 2026 in San Francisco, California, USA, on Wednesday, March 25, 2026...

An exploration of the interesting question.

There has been much discussion lately regarding the "Zero CVE" movement. At Red Hat, we welcome this focus, emphasized by our recent announcement of Project Hummingbird to provide more frequently updated container images. Hummingbird represents a shift in how customers receive Red Hat's open source artifacts: Faster without sacrificing code integrity. You can read more about Project Hummingbird here. While this project is relatively new, it's built on the years of work and lessons learned in modernizing our own internal build system.While the industry often focuses on the result (the image), w

Modern software development runs on open source, and that’s not hyperbole. Python alone pulls in dozens—sometimes hundreds—of third‑party libraries for even the simplest applications. While public repositories have fueled innovation at incredible speed, they’ve also created a new class of risk: Opaque build pipelines, unverifiable provenance, and a growing burden on teams to chase vulnerabilities after the fact.Today marks the tech preview of Red Hat trusted libraries, a new package index designed to bring enterprise-grade trust, transparency, and security posture to application depe

In the world of enterprise software security, few metrics are as coveted, or as elusive, as "zero CVEs." Simply put, a zero CVE (Common Vulnerabilities and Exposures) approach aims to deliver software components that are completely free of known security vulnerabilities at the time of shipping. For many organizations, particularly those in highly regulated industries, this is not just a "nice to have," it is a mandate. Initiatives like FedRAMP and various strict security frameworks increasingly demand that software supply chains be clean of known risks before deployment. As the industry has ta