Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How To Build An AI Risk Management Framework

Every AI approval a security team makes feels reasonable in isolation. A security architect signs off on a generative AI writing tool for marketing. An engineering lead spins up an agent to triage support tickets. A finance team connects a copilot to its planning software. Individually, none of these decisions looks risky.

How SLED can win the cybersecurity race with agentic AI

Adversaries are using AI to launch cyber attacks in record time, forcing security teams to measure responses in minutes instead of months. Phishing campaigns built with large language models (LLMs) achieve click-through rates 4.5 times higher than traditional methods,1 and the average time between initial compromise and lateral movement has fallen to just 29 minutes.2 This is a 65% increase from the prior year.2 State and local governments and higher education institutions are at an inflection point.

How autonomous pentesting kills false positives

Ask any security engineer what they actually think about their vulnerability scanner, and you will get a version of the same answer. They trust maybe 20% of what shows up in the patching queue. The rest gets a suspicious glance, and a slow death in a backlog. That is the real cost of a false positive. It is quiet, it compounds, and it hollows the tool out from the inside. It is also the reason autonomous pentesting came to replace hypotheses with confirmed exploits.

What Counts as One AI Asset? Getting the Unit Right

Two teams inventory the same organization and return different numbers. One counts forty-one AI assets, the other counts one hundred and twelve. Neither is wrong, because they counted different things, and nobody had decided what a row represents. ‍ Guidance on building an AI inventory covers which fields a row should carry and skips what a row is. That question determines the count, the risk scores, the regulatory classification and whether two inventories can ever be reconciled.

Secure AI Written Code Before It Ships: Salt Code

AI coding assistants are transforming how enterprise software gets built. Developers at every level are prompting their way to production-ready APIs, MCP integrations, and agentic workflows faster than any security team can review them. The problem is that none of those assistants knows your internal security standards, regulatory obligations, or risk tolerance. The result is insecure patterns shipping unnoticed, vulnerabilities discovered downstream when fixes are costly, and compliance becoming a guessing game on every commit.

451 Research report: How agentic AI is redefining identity security

In the short time that AI agents have been a part of the enterprise, they have upended many of our bedrock assumptions about the nature of identity, access, development, and work itself. At 1Password, we’ve been in the trenches of the agentic revolution; we’ve seen its positive impact on productivity, and the serious concerns it raises about security.

The Rise of the 'Non-Human Insider': When AI Agents Become the Threat

For years, cybersecurity has had a familiar villain: the external attacker. The hacker breaking through the firewall, stealing credentials or exploiting an unpatched vulnerability. It is the scenario we have trained for, built defenses around and spent decades trying to prevent. But the next major breach may not begin with someone breaking into your environment at all, it may begin with an AI agent that already has access.

Report: One-Quarter of Breaches Are Enabled by AI-Driven Attacks

A new report commissioned by IBM has found that one in four breaches is now AI-enabled, up 56% from last year. “Most AI-driven attacks reported in the study targeted critical infrastructure sectors (62%), with financial services and energy organizations experiencing the highest concentration, raising the risk of broader systemic disruption,” the report says. “Financial services breaches were reported to cost on average $6.3 million, while energy breaches cost on average $5.2 million.

Give your agents capabilities

Accelerating security solutions for small businesses‍ Tagore offers strategic services to small businesses. A partnership that can scale‍ Tagore prioritized finding a managed compliance partner with an established product, dedicated support team, and rapid release rate. Standing out from competitors‍ Tagore's partnership with Vanta enhances its strategic focus and deepens client value, creating differentiation in a competitive market.