We found a cluster of 1,001 IPs across 306 networks and 64 countries, tied to eight shared staging servers and a single TLS and HTTP fingerprint that appears nowhere else, plus smaller botnets that fall into clean separate islands.

I built an independent benchmark with 20 real CVEs across 15 CWE categories, 5 models (3 OpenAI, 2 Poolside Laguna), three prompt conditions: full advisory, behavioral description only, and location only (file and function, no description of the flaw).

I have three findings worth sharing:

• No model reliably fixes real vulnerabilities. The best solve rate (gpt-5.5) is 50% overall and 60% under the most favorable condition. The failure modes (e.g, wrong-search drift, budget exhaustion mid-implementation, plausible-but-incomplete patches that pass every visible test) are structured and repeatable across models and tasks.
• Token cost varies 4x for equivalent outcomes. The Laguna models consume 3–4x more tokens than OpenAI models of the same capability tier, with no improvement in solve rate.
• The locate condition is the benchmark's sharpest instrument. Give a model only a file and function (no description of the flaw). Every model drops. The differences between models are within noise at this scale, but it's the condition that most closely resembles what a security researcher actually does: reading code cold and recognizing independently that something is wrong.

Benchmark code and evaluation traces are open sourced.

This is a really bad one that flew under the radar. One character auth bypass in vLLM, LiteLLM, MCP servers, OpenAI shims, and a lot more.

A history of credentials at rest

I've been hard at work on a NEW phishing technique I'm excited to share. I'm calling it "Vaultjacking" and the impact is honestly a bit sobering.

In my blog I demonstrate how a single AiTM landing page can spoof your Google passkey/password manager PIN and use that to access ALL of a victim's third-party credentials (yes, including passkeys). A simple phish on one site can lead to a total compromise of all Chrome-saved credentials.

After FIOD seized 800+ servers and arrested two operators on May 18, the ELLIO research team reports that scanning from the network's ASN ranges has continued largely uninterrupted - and that while roughly a third of the recently-active ranges (including the legacy Stark blocks 94.131.105.0/24 and 92.118.232.0/24) have since been withdrawn from global routing, the surviving ranges under AS209847 (WorkTitans / THE.Hosting) are still announced and still scanning, at the network's normal daily rate.

The sibling ASNs (AS213999 and the Moscow-based AS33993) remain routed and idle.

The recent activity skews toward database and ICS/SCADA discovery = MongoDB, Redis, PostgreSQL, Oracle, LDAP, plus DNP3 and EtherNet/IP - alongside known-exploit probes like CVE-2017-17215 and WinRM.

The Lithuanian Prosecutor General’s Office and the Criminal Police Bureau have initiated a joint investigation into a large-scale data exfiltration incident targeting the State Enterprise Centre of Registers. The incident involved the unauthorized copying of over 600,000 records from the country's national Real Estate and Legal Entities Registers.

Rather than exploiting an unpatched software vulnerability, the attack mechanics rely on a classic trust-boundary compromise.

The Entry Vector: Cross-Agency Credential Misuse (MITRE T1078)

Forensic tracking indicates that the threat actors executed a series of unauthorized connections originating from foreign infrastructure. The entry vector relied on valid, high-privilege B2B institutional login credentials assigned to external state departments authorized to query the central registry database.

Independent statements from legislative and defense officials suggest the specific access pathway was carved out by compromising authenticated accounts belonging to the Department of Migration under the Ministry of the Interior. By hijacking these valid inter-agency connection points, the threat actors bypassed perimeter barriers, allowing them to issue massive queries to the backend database without triggering immediate anomaly blocks.

Exfiltration Scope & Impact Profile

The breach was initially identified by internal monitoring in early April 2026, but public disclosure was delayed due to the ongoing criminal inquiry. The exfiltrated data schemas consist of:

• Full legal names, dates of birth, and unique national identification numbers.
• Registered physical addresses, corporate entity structures, and detailed cadastral/property registry extracts.

The Centre of Registers has confirmed that primary consumer-facing vectors - such as telephone contact details, email addresses, bank account numbers, or raw cadastral measurement files - were not part of the exfiltrated datasets.

The primary operational risk is tactical intelligence gathering. Security analysts have pointed out that bulk access to unlisted residential addresses linked to legal entities can be leveraged by foreign intelligence services for target profiling, spear-phishing orchestration, or coercion of state personnel, diplomats, and military figures.

Incident Response & Remediation

Following the identification of the unauthorized bulk queries, the Centre of Registers implemented the following controls:

1. Immediate revocation and blocking of all compromised inter-agency institutional accounts.
2. Mandatory credential rotation and strict query-volume throttling across all API and web self-service gateways linked to external state dependencies.
3. The director of the Centre of Registers, Adrijus Jusas, formally stepped down on May 25 following administrative scrutiny regarding legacy IT infrastructure and monitoring gaps.

While independent defense officials note the incident matches the operational signatures of state-aligned hybrid surveillance operations, official attribution from the Prosecutor General's Office remains open.