home.social

Search

5 results for “hasamba”

  1. ----------------

    🎯 AI
    ===================

    OX Security published a research report covering 15,465 published MCP servers and 5,095 unique hostnames. The short version: the Model Context Protocol ecosystem has no native governance for data residency, domain lifecycle, or permission persistence, and a prompt injection test against Claude Code succeeded under one specific model configuration.

    🔹 Research Scope

    The team enumerated 15,465 published MCP servers and resolved 5,095 unique hostnames behind them. Coverage falls into three buckets: geolocation of resolved infrastructure, domain registration and resolution state, and servers sitting on consumer-grade network paths. A separate test checked whether a granted permission in Claude Code survives a subsequent prompt injection.

    🔹 Key Findings
    • Data residency: 15.6% of analyzed hostnames resolved to infrastructure outside the US, including infrastructure in China and Russia. MCP currently provides no native protocol mechanism to enforce where connected tools run or where data is processed, so residency enforcement is left entirely to the deploying side.
    • Consumer infrastructure: 0.45% of hostnames were associated with home networks or consumer tunneling tools. Agent workflows can therefore reach endpoints that never crossed corporate network controls, which breaks standard visibility assumptions.
    • Domain takeover: 2.3% of hostnames failed to resolve. Six of the underlying domains are unregistered and available for around $4 per year. If MCP clients or workflows keep trusting and calling those names, whoever registers them can stand up a matching server and inherit the traffic. It is the classic dead-domain takeover problem, showing up one layer above the web.
    • Permission persistence: In testing against Claude Code with Haiku 3.5, a single 'Always-Allow' grant was enough for a malicious MCP server to follow up with prompt injection and execute privileged file access without another user confirmation. The same attack did not succeed against Opus 4.6 or 4.7, so the result appears model-dependent, and it comes from the vendor's own testing.

    🔹 Analysis

    The takeover finding is the mechanically simplest one. Published MCP server listings operate as a de facto trust directory, but nothing in the protocol verifies that a hostname still belongs to its original operator. A handful of $4 registrations is close to the cheapest infrastructure acquisition available, and the public summary describes no pinning or allowlist control that would stop it.

    The residency numbers matter mostly because agent workflows call these hostnames automatically. If a connected tool resolves to infrastructure in a jurisdiction the organization never approved, nothing in MCP surfaces that to the user or the admin at connection time.

    The Claude Code result deserves the most caution. Permission scoping, exact prompts, and injection payloads are not described in the public summary, and the gap between Haiku 3.5 and Opus 4.6/4.7 has no published root cause. It is a reasonable hypothesis that smaller models tolerate injected instructions over an existing allow, but that is a hypothesis, not a confirmed mechanism.

    🔹 Operational Notes

    Translating findings into checks: inventory which MCP hostnames your clients actually resolve, geolocate them, flag anything dead or sitting on consumer tunneling, and review how client-side 'Always-Allow' grants are scoped. None of that is enforced by MCP itself today. The report does not publish a defense list in the summary, so these are the checks its own findings point at.

    🔹 Limitations

    This is vendor research from OX Security. The public summary omits the full methodology, the hostname list, and any detection coverage. The percentages should be treated as indicative until reproduced, and the prompt injection result has not been independently tested.

    🔹 MCP

    🔗 Source: ox.security/ebooks/15465-mcp-s

  2. ----------------

    🛠️ Tool
    ===================

    herdr web ui: a browser and phone client for herdr

    herdr web ui is an open source web client (GitHub: devswha/herdr-web-ui, MIT license) for herdr, a tool that runs AI coding agent sessions in a terminal-based workspace layout. The client exposes those same sessions in a browser or on a phone as an installable PWA, so a Claude Code or Codex session running on the desktop machine can be read and answered from anywhere. The README tagline states the value plainly: Claude Code and Codex, from your phone.

    Key features
    • Chat view for agent prompts. When Claude Code asks a question in herdr's terminal, the same question appears in the browser and on the phone, and one tap on the phone answers it. The README documents this with live recordings, including captions describing the mirrored question and single-tap reply.
    • Live terminal passthrough. One click turns the chat into the pane's real terminal. On mobile, a key bar includes ↑ to recall the previous command, and Enter on the input line runs it. The recorded demo reruns bun test: 5 pass, 0 fail.
    • Full layout mirroring. The sidebar shows workspaces with per-agent state, for example checkout-api DONE, web-dashboard RUN, infra READY. Tabs hold panes, split panes list both members (tests and git), and a git pane exposes git log.
    • Alerts. The phone can show another workspace's terminal while Claude runs in a different one. The retrieved README cuts off mid-section here, so the alert mechanics are only partially documented.
    • PWA install. The client is installable on the phone as a Progressive Web App.

    Technical implementation

    The client requires herdr 0.9.0 or newer and connects to a running herdr instance; the agents themselves stay on the machine that runs herdr. The project ships a hosted website, an interactive demo instance, a quick-start guide under docs/guide.md, and README translations in Chinese, Japanese, and Korean. Notably, the README portion retrieved here ends before the install, FAQ, and docs sections, so the transport and authentication model between browser and herdr is not described in the source material. That gap matters: a browser surface into a terminal that runs coding agents is exactly the kind of component whose authentication and network exposure deserve scrutiny, and nothing in the visible text verifies either side.

    Use cases
    • Approve agent questions from the phone without SSH to the desktop.
    • Monitor several agent workspaces from one browser window and read agent state at a glance.
    • Rerun a test suite from the phone after an agent edits code, then return to chat.

    Installation and setup

    The visible README points to a quick-start guide and a hosted demo, and marks the client as an installable PWA. The actual install steps sit in the docs section that was not included in the retrieved content.

    Limitations
    • Hard dependency on herdr 0.9.0+ running on the machine with the agents.
    • Security posture of the browser-to-herdr connection is undocumented in the visible portion.
    • The alerts feature is only partially described in the source available here.

    Haven't tested this personally. The choice to ship live recordings with captions describing exact test counts is a reasonable credibility signal, but the authentication question is the first thing to check in the full docs before relying on this from outside the local network.

    🔹 herdr #ClaudeCode #Codex #PWA #tool

    🔗 Source: github.com/devswha/herdr-web-ui

  3. ----------------

    The ultimate guide to multi-harness RL - a Hugging Face Space by FineEnvs

    🔗 Source: huggingface.co/spaces/FineEnvs

  4. ----------------

    🛠️ Tool
    ===================

    Get-NetScalerTimeline: automated file system timelines for NetScaler ADC/Gateway disk images

    Get-NetScalerTimeline.ps1 is a Windows-based DFIR utility from LETHAL-FORENSICS that builds a file system timeline directly from a NetScaler VMDK disk image. It detects the FreeBSD slice and its UFS partitions automatically, keeps native tool output byte-for-byte, normalizes timestamps to UTC ISO 8601, and imports the bodyfile into DuckDB so the result can be hunted with SQL. The stated focus is the persistent locations used by web shells and the log poisoning technique associated with CVE-2026-88771.

    Key features
    • Partition detection: finds the FreeBSD slice (0xa5) and all UFS partitions under its BSD disk label, including mount points such as /flash and /var.
    • VMDK handling: flat extents (*-flat.vmdk), descriptor files, and split images across multiple extents.
    • Timeline output: bodyfile via fls and timeline via mactime, UTC ISO 8601, exported as CSV and XLSX.
    • DuckDB import: file type, allocated versus deleted status, orphan files, symlink targets, and human-readable timestamps; an interactive DuckDB UI session opens at the end of the run.
    • Log extraction: ns.log, httpaccess.log, and httperror.log pulled byte-for-byte from the image, including rotated .gz archives, with SHA256 hashes of the evidence copies.
    • Log poisoning detection: a search for fake pitboss heartbeat messages followed by shell operators, mapped to CVE-2026-88771.
    • Log coverage reporting: shows how far back the local logs reach, since NetScaler rotates its logs quickly.
    • Optional hashing: MD5 and SHA256 over allocated regular files, read from the image and hashed in memory with no file extraction.
    • Evidence hygiene: non-UTF-8 filenames preserved, pipe characters in filenames handled, PowerShell re-encoding avoided entirely.

    Dependencies and platform

    Pinned versions per the README: The Sleuth Kit 4.14.0, Strawberry Perl 5.42.3.1, DuckDB CLI 1.5.6, and the ImportExcel PowerShell module 7.8.10. Tested on Windows 11 Pro x64 with Windows PowerShell 5.1 and PowerShell 7.6.6. Expect to re-validate these versions against current releases before deployment.

    Evidence collection caveats

    The collection guidance in the README is worth repeating: volatile data first. Generating an NSPPE core dump restarts the NetScaler and wipes the RAM disk (/etc, /netscaler), so run a live triage collection before triggering the dump. The dump itself is written to /var/core, which means free space on /var should be verified beforehand.

    Use cases
    • Post-imaging triage of suspected NetScaler compromises, with SQL queries over web shell persistence locations on /flash and /var.
    • Auditing how much local log history survived rotation before deciding whether to pivot to remote log sources.
    • Verifying CVE-2026-88771 log poisoning activity through the pitboss heartbeat heuristic.
    • In-memory hashing of allocated files for quick malware screening.

    Limitations

    Windows-only workflow with pinned dependencies. Fast log rotation means short local coverage; the tool surfaces the gap rather than solving it. Analysis runs against an image, so volatiles need a separate collection step. Haven't tested it personally against a real image; worth validating on lab snapshots before relying on it in a case.

    On paper, the DuckDB integration and the byte-for-byte evidence handling are the parts worth noting; validation on real images will tell.

    🔹 DFIR #tool #NetScaler #DuckDB #Forensics

    🔗 Source: github.com/LETHAL-FORENSICS/Ge

  5. ----------------

    🛠️ Tool
    ===================

    Velociraptor Skills is a public GitHub repository (ig-labs/velociraptor-skills) providing reusable Codex skills and DFIR tooling for Velociraptor operations. It covers setup, collection, hunting, and host analysis workflows.

    Key Features

    The repository includes eight distinct skills:
    • prep-dfir-tools - prepares DFIR tooling environment
    • velociraptor-artifact-selection - artifact selection guidance
    • velociraptor-collection - evidence collection workflows
    • velociraptor-engagement-setup - engagement configuration
    • velociraptor-host-analysis - host-level forensic analysis
    • velociraptor-hunting - hunt-based detection operations
    • velociraptor-live-api-client - live API interaction
    • velociraptor-mapped-client - mapped evidence handling

    A shared ./vraptor runtime supports all skills, along with bounded custom-agent templates and installation helpers.

    Technical Implementation

    The default setup connects to an existing live Velociraptor server and uses the OpenAI API for analysis. Prerequisites include Python 3.11+, Git, a server administrator's API-client YAML, and an OpenAI API key. Credentials are stored outside the checkout directory.

    Multiple server connections are supported within a single installation. Each server gets its own reference name and API-client YAML path. The --server-profile flag selects the connection per command.

    For live-remote mode, the setup command vraptor setup start --mode live-remote --id ir1234 --server-profile "<SERVER REFERENCE>" handles server maintenance or hunt review without requiring a hostname or visible client.

    Codex and Claude Code Integration

    Skills are linked separately via ./utils/link-codex-skills.sh for Codex and ./utils/link-claude-skills.sh for Claude Code. The linking creates symlinks, so the checkout must remain available. Existing symlinks are updated; real files are preserved and reported as conflicts.

    Limitations

    Remote API access requires no local Velociraptor binary, SSH connection, or Codex login. However, offline checks do not prove live authentication. Explicit connection and AI tests are documented in the installation guide. The repository includes a public release review covering import scope, sanitization, and validation results.

    The --no-configure flag skips the setup wizard during upgrades, and --no-path handles dependency-only installation or CI environments.

    🔹 tool #velociraptor #dfir #codex #incident_response

    🔗 Source: github.com/ig-labs/velocirapto

Share on Mastodon

Enter the server where you have an account.