Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Five Ways AI Agents Actually Fail, and Why Most Security Programs Are Only Built for Two of Them

Most of the industry discourse on agentic AI risk has settled into a comfortable framing: agents get attacked the way models get attacked, through some form of prompt manipulation, and the fix is a better guardrail. I think that framing is dangerously incomplete, and I want to walk through five specific scenarios that make the case directly rather than abstractly. Two of them are manipulation. One exploits trust between agents rather than any single agent's behavior.

Top 5 Antidetect Browsers for Web Scraping, Research, and Data Collection at Scale

Modern web setup needs strong anti-bot tools. These tools look at what comes in from the web, the browser settings, and what the canvas shows to find bots. People who work in company growth, data, and research often need to pull data from the web. For them, normal headless browsers like Puppeteer or Selenium are easy to spot. To get data many times, you will need tools that can hide your system details in several sessions at once.

5 Best Direct Mail APIs for Automated, Multi-Touch Campaigns

Email has triggers, sequences, and dashboards. For years, direct mail had a spreadsheet and a print deadline. A good direct mail API closes that gap: your software decides who gets a mailpiece and when, and the provider prints, mails, and tracks it. The catch is that "best" depends on the job. A product team embedding transactional notices needs something very different from a marketing team running three-touch campaigns across dozens of clients. I compared Postalytics, Lob, PostGrid, PCM Integrations, and Click2Mail on the factors that actually separate them.

Zero Trust for AI Agents: Enforcing Anthropic's Framework

AI has changed how work gets done. Agents can plan tasks, query enterprise repositories, invoke tools, write code, call application programming interfaces (APIs), and take actions across connected systems. As they work, they create, copy, fragment, transform, and share data across workflows. A perimeter and a one-time authorization decision do not provide enough control for this operating model. An agent can chain permissions, tools, integrations, and data sources while completing a task.

Request, Aggregate, Bypass: How Attackers Can Evade LLM Safety Classifiers

Modern frontier AI models deploy safety classifiers. These are second AI models that sit between the user and the frontier model, evaluating every request in real time. If a request is flagged as harmful, the classifier blocks it before the model can respond. Significant investment and safety model expertise have made these classifiers effective. Anticipating how adversaries circumvent these systems is a security problem that requires different expertise.

AI Governance Where the Regulator Also Runs the Market

AI governance evidence is usually prepared for a neutral reader. A regulator with no stake in the market, an auditor with no competing product, an examiner who gains nothing from what the documentation contains. ‍ In securities and derivatives markets that assumption does not hold. Exchanges and clearing organizations register as self-regulatory organizations, and most of them operate the market while regulating its participants. The reader of your evidence is also an operator. ‍