Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Rethinking the Interception Proxy: Why Crusader is Betting on Local-First SQLite

For years, interception proxies have largely followed the same formula. Capture traffic, display requests, allow replay and modification, and store everything inside an internal project format. It is a workflow that has served penetration testers and bug hunters well, but it also creates an unexpected limitation: the data you generate during an assessment often becomes surprisingly difficult to use outside the proxy itself.

What is KeeperDB?

KeeperDB is a secure, multi-protocol database client built on Keeper’s zero-knowledge platform. Available as both a free standalone desktop application and a privileged session component of KeeperPAM, KeeperDB combines a database query engine, vault-managed credentials, real-time performance monitoring and an AI-powered database assistant in a unified interface. Continue reading to learn more about how KeeperDB works, its key features and the benefits of using it to help secure database access.

PostgreSQL: How to Control and Audit Agent Access with Identity

AI agents querying databases pose well-documented risks. What gets less attention is the fact that PostgreSQL has no native concept of an agent as a distinct actor. This means DBAs are managing access for something that appears in pg_stat_activity like any other role created with CREATE ROLE, with no distinguishing attributes and no indication of who or what initiated the connection. AI agents have no distinct identity when interacting with PostgreSQL.

How KeeperDB Secures Database Access

Database access is one of the largest blind spots in enterprise security. Credentials are often shared, insecurely stored or transmitted without monitoring. KeeperDB is a modern, multi-protocol database client that addresses these gaps by supporting PostgreSQL, MySQL, Microsoft SQL Server and other major protocols from a unified interface.

Zero Trust in SaaS Development: Architecting Multi-Tenant Systems for Compliance

In a multi-tenant SaaS environment, perimeter defense is a dangerous illusion. If a threat actor gets through the outer wall or a developer makes one routing mistake, every tenant's data is at risk. Application logic alone is not enough to separate tenant data. A single misconfigured query or a SQL injection attack can expose data that was never meant to be seen. In regulated industries like FinTech and Healthcare, that kind of exposure hurts your customers and triggers audits, fines, and investigations.

How to Eliminate Shared Database Passwords: MySQL, PostgreSQL, and More

Traditionally, engineers have relied on shared database passwords. When someone needs to run a query, they either already have standing access granted via a static credential everyone on the team knows, or someone has to scramble to create a quick workaround. Every new user, exception rule, or port forward through a bastion host becomes a “just this once” fix.

Redis Use-After-Free Remote Code Execution Vulnerability (CVE-2026-23479)

In May 2026, Redis disclosed a high severity memory safety vulnerability tracked as CVE-2026-23479. The issue affects the Redis server, a widely deployed in memory data structure store used for caching, messaging, and real time analytics across cloud and on premises environments. The vulnerability exists in the client unblocking logic and may allow an authenticated attacker to achieve remote code execution under specific conditions.

How to Prevent SQL Injection Attacks (2026): 7 Proven Techniques

Your database is one apostrophe away from a breach. SQL injection has been the most common web vulnerability for three consecutive years. The 2025 Verizon DBIR reports it contributed to 12% of all data breaches, up from 9% the year before. In December 2024, a PostgreSQL SQL injection zero-day gave state-sponsored attackers a path into the US Treasury. In 2023, a single campaign used it to steal 2 million job seeker records across 65 websites in one month. The fix has been known for two decades.

Why You Shouldn't Use LLMs to Generate SQL (Security Risks)

“Just let the LLM write the SQL.” It sounds powerful. A user types a question in plain English, the model generates a query, the system runs it against the database, and the answer comes back. No SQL knowledge required. No BI tools. No waiting for the data team. It works beautifully in demos. And it is a serious engineering mistake in production. Direct SQL generation from LLMs combines two things that should never be combined: untrusted code generation and privileged execution.