The Security Boulevard stories enterprise IT leaders actually read.
Volume 343, Issue 3 · 11 articles
A ransomware primer: the typical attack sequence, warning signs to monitor and ten prevention controls. Seceon-authored.
This Seceon post outlines the typical ransomware sequence of initial access, discovery and persistence, privilege escalation and lateral movement, data exfiltration and encryption.
Warning signs include unusual file changes, unexpected admin tool use, attempts to disable security controls, suspicious privilege changes and abnormal outbound traffic.
It lists ten prevention measures, including patching, MFA, least privilege, EDR, segmentation, tested offline or immutable backups, phishing training, remote access protection, centralized logging and an incident response plan, citing CISA's StopRansomware guide.
The second half promotes Seceon's platform without independent test data.
Credentials, code, customer records and financials dominate AI-tool leakage; each needs a different detection approach. Kovrr post.
Kovrr argues four data categories account for most of what leaves organizations through AI assistants.
Credentials are easy to detect by their high-entropy prefixes and can be blocked outright, while source code is common to paste, so it should trigger a warning rather than a block unless it contains internal hostnames or package names.
Customer records should be flagged by record count, not by any personal data, and financial material can only be caught through provenance, such as a paste shortly after a finance export.
Traditional DLP misses browser pastes, so this vendor-authored post proposes in-browser classification that sends only metadata off the device.
A SIEM buyer's guide covering requirements, detection quality, scale, integrations, TCO and a weighted proof-of-concept scorecard. Seceon post.
This Seceon buyer's guide recommends starting a SIEM selection with an inventory of risks, systems and measurable goals before comparing vendors.
Evaluation areas include log source coverage, rule-based and behavioral detection, scrutiny of AI and ML claims, alert quality, scalability, deployment model, integration with EDR, XDR and SOAR, threat intelligence, compliance reporting, multi-year total cost and vendor support.
It suggests an illustrative weighted proof-of-concept scorecard, such as 20% for detection quality, and lists common purchasing mistakes and a 14-item checklist before promoting Seceon's own platform.
Vendor-authored.
Checkpoint reviews can't keep up with AI agents; Wallarm argues for continuous governance with defined permissions and runtime monitoring.
In this vendor-authored response to a Brookings and World Economic Forum analysis, Wallarm's Tim Erlin argues the key questions for AI agents are what an agent did, whether it was authorized and who is accountable.
Stage-based reviews fail because agents invoke tools and act before humans look, so governance should be continuous, with permissions defined in advance, verifiable evidence and runtime monitoring.
He cites a Gartner prediction of more than 150,000 agents at the average Fortune 500 firm by 2028, with only 13% of organizations confident in their governance, and notes EU high-risk AI rules are delayed to 2027-2028.
He proposes Discover, Observe, Enforce and Govern steps.
Top-down and bottom-up cyber risk models give predictably different numbers, and the gap itself reveals inventory and control gaps.
Kovrr explains that top-down cyber risk quantification uses revenue, sector, headcount and maturity benchmarked against peer losses and can produce a figure within days, while bottom-up models need a full asset inventory with values, interruption costs and control coverage.
Bottom-up estimates usually come in lower because they count only inventoried assets and treat them as independent, while top-down estimates run higher because sector benchmarks include weaker peers.
A bottom-up figure far below top-down suggests missing assets or strong controls, and one above it suggests double counting.
Top-down suits insurance and board reporting and bottom-up suits control funding, the vendor-authored post concludes.
Tenable and OpenAI now vet community-contributed security agents for prompt injection, hardcoded secrets and data exposure.
Tenable, working with OpenAI, added an Exchange Inspector that evaluates open source AI agents contributed to its CyberAgents Exchange directory.
An inspection engine checks for malicious content such as prompt injection and for hardcoded secrets or exposed customer data, followed by an assessment with OpenAI's GPT cyber models and a review by Tenable researchers.
Three skills have been vetted so far, including a SOC Hunter agent Tenable says cuts threat-hunting time by up to 75% and a daily remediation planning agent.
Michael Vizard notes adoption is unclear and that shared agents still need strict guardrails and access controls.
Aembit profiles nine MCP security platforms across identity, gateways, runtime detection, tool authorization and discovery.
This vendor-authored Aembit post divides MCP security into identity and access control, gateway and routing, runtime threat detection, tool-level authorization and discovery of MCP servers and clients.
It recalls a 2025 Invariant Labs finding in which a malicious GitHub issue led an agent to leak private repository data through the official GitHub MCP server.
It profiles Aembit, Runlayer, Lasso Security, Invariant Labs/Snyk, Pillar Security, Wiz, TrueFoundry, MintMCP and Cisco AI Defense, ranking Aembit first.
It advises choosing by the problem to be solved, noting most organizations will need several capabilities.
Risk assessment tools split into GRC, vulnerability management, CRQ and free public tools; mature programs combine several. Kovrr post.
Kovrr argues no single platform covers every risk assessment need and divides the market into four categories: GRC platforms for framework mapping and audits, vulnerability management for infrastructure scanning, cyber risk quantification for financial exposure, and free tools such as CISA CSET, with more than 50 modules, and NIST CSF 2.0 templates.
Key capabilities include continuous data ingestion, alignment with NIST CSF 2.0, ISO 27001 and DORA, and executive reporting.
It warns that labor often dominates total cost and says mature programs layer tools with CRQ on top.
Vendor-authored, closing with a demo offer.
Seceon compares eight continuous compliance monitoring platforms, including Wiz, Drata and Vanta, and ranks its own product first.
Arguing that annual audits no longer suffice for hybrid cloud compliance, this Seceon post compares eight continuous compliance monitoring platforms: Seceon aiCompliance CMX360, Microsoft Defender for Cloud with Purview, Palo Alto Cortex Cloud, Wiz, ServiceNow GRC, Qualys Policy Audit, Drata and Vanta.
It says most competitors focus on one evidence domain such as cloud configuration or audit workflow, notes Drata syncs nightly and Vanta tests hourly, and ranks its own product first, citing vendor-reported cuts of up to 90% in manual effort.
It closes with an eight-point buyer checklist.
Vendor-authored comparison.
Expert, deterministic and probabilistic CRQ models compared; choose by the data you hold and the decision you need to support. Kovrr post.
Kovrr describes three types of cyber risk quantification model: expert judgment, which is subjective; deterministic, which is simple but ignores uncertainty; and probabilistic, which uses methods such as Monte Carlo simulation to produce a range of outcomes.
A worked example shows an 80% chance of a $1 million loss and a 10% chance of a $30 million loss.
FAIR is common in large enterprises but slow and manual, while platforms using external loss data can return results in 24 to 48 hours.
The vendor-authored post says model choice depends on available data and the decision at hand, and recommends quarterly reassessment.
With PAM vendors consolidating, start migration six to eight months before renewal and run both platforms in parallel. 12Port post.
Acquisitions are consolidating the privileged access management market and can change the licensing, support and roadmap customers bought, so 12Port lays out a migration plan in this vendor-authored piece.
Start six to eight months before contract expiry, or a year for large enterprises, remembering notice periods of 60 to 90 days.
The timeline covers assessing the current platform, evaluating vendors, running a proof of concept, selecting and planning a phased migration.
Run both systems in parallel for two to three months with one platform owning each credential's rotation, confirm audit records and emergency access before decommissioning, and negotiate short extensions rather than rush.
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