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  1. Silent Lynx Exploits WinRAR Flaw to Deploy Reverse Shell in CIS Government Attacks

    The threat actor known as Silent Lynx has been attributed to a fresh set of attacks targeting government organizations across the Commonwealth of Independent States. The activity, observed from June 2025 through August 2026, uses four infection chains including macro-enabled documents, GitHub-hosted PowerShell, and crafted WinRAR archives. thehackernews.com/2026/10/sile

  2. I forgot to post this earlier, but I'm now live with Silent Hill Townfall! Let's find out what nightmares lurk in the fog!
    twitch.tv/capsulejay

  3. Security researchers attribute a series of targeted attacks against government organizations in the CIS to the threat actor Silent Lynx.

    The campaign, observed between June 2025 and August 2026, utilized four distinct infection chains leveraging macro documents, PS2EXE downloaders, GitHub-hosted PowerShell, and crafted WinRAR archives exploiting CVE-2025-8088 to deploy custom reverse shells like FoalShell, Chvost, Laplas, and P…

    en.hacks.gr/omada-chaker-katas

    #SilentLynx #Malware #PowerShell #WinRAR

  4. Silent hunter of the night, the Western Barn Owl's (Tyto alba) heart-shaped face gathers the faintest sounds, while extraordinary hearing and virtually silent flight make it one of nature's most accomplished nocturnal predators.

    Courtesy: Fiyin

  5. Silent Ransom Group Chat Leak: What It Reveals packetstorm.news/news/view/454

  6. Detect Silent Model Drift With a Stdlib-Only Golden Set Harness


    A hosted model can change between two of your deploys, and nothing in your lockfile moves. Your unit tests still pass, your container still builds, and your users still get slightly different JSON than they got last Tuesday. The practical fix is not a bigger test suite; it is a frozen golden set, a deterministic scorer, and an append-only ledger that fails the run when the pass rate drops below a floor.

    This article builds exactly that, using only the Python standard library. It runs on a free-tier host, it costs one file of input data, and it answers a single narrow question: did the contract my product depends on stop holding?

    Why ordinary tests miss model drift


    Application tests assert on code you control. A model response is an input from outside your repository, and it arrives as free text that happens to be parseable.

    When a provider adjusts decoding defaults, swaps capacity, or routes you to a different checkpoint, the shape of the output can shift while the API status code stays 200. Nothing throws. The failure surfaces later, as a support message about a field that used to be filled in.

    A golden set inverts that. Instead of asserting on the current behavior, it asserts on a small number of hand-checked examples that were correct on a specific day, and it keeps the receipts.

    Step 1: Freeze a small golden set as JSONL


    The input file is plain JSONL, one contract per line. Keep it small on purpose: 20 to 40 cases is enough to catch a formatting or label flip, and it fits inside a free-tier request budget.

    {"id":"invoice_date","input":"Invoice paid 2026-03-04, net 30 days.","expect":{"label":"invoice","fields":{"due_date":"2026-04-03"}}}
    {"id":"refund_request","input":"I want my money back for order 8812, it never arrived.","expect":{"label":"refund","fields":{"order_id":"8812"}}}
    {"id":"no_action","input":"Thanks, the docs answered my question.","expect":{"label":"none","fields":{}}}

    Every line has three parts: an id you will grep for in the ledger, the raw input you send, and the expect object you compare against. Do not paste generated examples into this file. If you did not read the output and agree with it, it does not belong in the baseline.

    Step 2: Write a transport adapter that assumes nothing


    The runner below assumes an OpenAI-style /chat/completions request body. That assumption is isolated in one function so you can replace it when your endpoint differs.

    #!/usr/bin/env python3
    """golden_run.py - regression run against a chat endpoint. Stdlib only."""
    import json, os, sys, time, hashlib, pathlib, urllib.request

    BASE = os.environ["MODEL_BASE_URL"].rstrip("/")
    KEY = os.environ["MODEL_API_KEY"]
    MODEL = os.environ["MODEL_ID"]
    GOLDEN = pathlib.Path(os.environ.get("GOLDEN", "golden.jsonl"))
    LEDGER = pathlib.Path(os.environ.get("LEDGER", "ledger.jsonl"))

    SYSTEM = (
    "You are a strict extractor. Return ONLY minified JSON shaped as "
    '{"label": string, "fields": object}. Omit absent fields. '
    "No prose, no markdown fences."
    )

    def call(text, timeout=30):
    body = json.dumps({
    "model": MODEL,
    "temperature": 0,
    "messages": [{"role": "system", "content": SYSTEM},
    {"role": "user", "content": text}],
    }).encode()
    req = urllib.request.Request(
    f"{BASE}/chat/completions", data=body,
    headers={"Content-Type": "application/json",
    "Authorization": f"Bearer {KEY}"},
    )
    with urllib.request.urlopen(req, timeout=timeout) as r:
    payload = json.loads(r.read())
    return payload["choices"][0]["message"]["content"]

    Keep temperature at zero when the endpoint supports it. If the parameter is rejected or ignored, note that in your README rather than deleting it, because a later comparison depends on knowing what you actually sent.

    Step 3: Score the contract, not the prose


    Scoring is exact after light normalization: trim, lowercase, collapse whitespace. That is deliberately unforgiving, because the goal is to detect change, not to grade writing.

    def norm(v):
    return " ".join(v.strip().lower().split()) if isinstance(v, str) else v

    def score(case, raw):
    try:
    got = json.loads(raw)
    except json.JSONDecodeError:
    return {"case": case["id"], "ok": False, "why": "invalid_json"}
    want = case["expect"]
    if norm(got.get("label")) != norm(want["label"]):
    return {"case": case["id"], "ok": False, "why": "label",
    "got": got.get("label"), "want": want["label"]}
    fields, gotf = want.get("fields", {}), (got.get("fields") or {})
    for k, v in fields.items():
    if norm(gotf.get(k)) != norm(v):
    return {"case": case["id"], "ok": False, "why": f"field:{k}",
    "got": gotf.get(k), "want": v}
    return {"case": case["id"], "ok": True, "why": "pass"}

    Two failure reasons are distinguishable here and that distinction is the whole point: invalid_json is a format drift, label or field:* is a content drift.

    Step 4: Append every run to a ledger and exit non-zero


    The ledger is one JSON object per line, append-only, with a run_id derived from the system prompt, model id, and base URL. Change any of those and the id changes, which keeps old and new comparisons honest.

    def run():
    run_id = hashlib.sha256(
    (SYSTEM + MODEL + BASE).encode()).hexdigest()[:12]
    rows =
    [] for line in GOLDEN.read_text().splitlines():
    line = line.strip()
    if not line or line.startswith("#"):
    continue
    case = json.loads(line)
    raw, err = "", None
    for attempt in range(3):
    try:
    raw = call(case["input"])
    break
    except Exception as exc: # timeout, 429, DNS, 5xx
    err, raw = repr(exc), ""
    time.sleep(2 ** attempt)
    if not raw:
    rows.append({"case": case["id"], "ok": False,
    "why": "transport", "err": err})
    continue
    r = score(case, raw)
    r["raw"] = raw[:400]
    rows.append(r)
    total, passed = len(rows), sum(r["ok"] for r in rows)
    rate = round(passed / total, 3) if total else 0.0
    record = {"run_id": run_id, "ts": int(time.time()), "total": total,
    "passed": passed, "rate": rate, "rows": rows}
    with LEDGER.open("a") as fh:
    fh.write(json.dumps(record) + "\n")
    print(f"{passed}/{total} ({rate:.0%}) run_id={run_id}")
    floor = float(os.environ.get("PASS_FLOOR", "0.9"))
    return 0 if total and rate >= floor else 1

    if __name__ == "__main__":
    sys.exit(run())

    Exit codes matter more than dashboards when you are alone. Non-zero from this script can page you, block a deploy, or simply stop a scheduled job from marking the day green.

    Step 5: Run it on a schedule without paying for a scheduler


    On a free-tier host, cron is the cheapest scheduler you have. Secrets stay in a .env file that the job sources, so the crontab itself contains no keys.

    # /srv/app/run-golden.sh
    set -euo pipefail
    cd /srv/app
    set -a; . ./.env; set +a
    python3 golden_run.py >> /var/log/golden.log 2>&1

    # off-peak, once a day; adjust to the hour your host is quietest
    17 4 * * * /srv/app/run-golden.sh

    Compare the last two runs with one command. The jq filter prints only the cases that flipped.

    tail -n 2 ledger.jsonl \
    | jq -c '{run_id, ts, rate, fails: [.rows[] | select(.ok == false) | .case]}'

    Free-tier containers often sleep between requests. A 30-second timeout and a three-attempt backoff absorb most cold-start noise, and the transport reason keeps that noise out of your content-drift count.

    Reading the ledger: a decision table

    Signal in the ledgerLikely causeFirst actionMany transport, few content failuresthrottling, cold start, or a slow windowMove the job off-peak, lower case count, raise timeoutSudden invalid_json on every caseresponse formatting default changedRe-check the adapter and system prompt before blaming the modelOne field fails on most casesreal content changePin a previous model id if one is offered, or add a normalization stepOne case fails, everything else passesa genuinely hard exampleRe-read the expected value; the baseline may be wrong


    A single bad run is not a verdict. Two consecutive runs with the same failure set is the threshold worth acting on.

    Limitations and who should skip this


    Exact-match scoring is brittle by design and wrong for open-ended generation. Do not point this harness at a summarizer, a chat assistant, or anything whose value is in the phrasing.

    A 20-to-40 case set cannot detect rare failures, and it gives no statistical confidence. Teams that need eval coverage, graders, or per-release reports should use a real evaluation platform instead.

    The adapter is single-turn. Agents that call tools across multiple round trips need a different harness, or at least a recorded-transcript replay layer in front of this one.

    Finally, the runtime budget is real. Free-tier quotas, sleep windows, and timeouts change; the ledger tells you when they did, but it will not make them go away.

    Where MonkeyCode fits in this loop


    Disclosure: This article was prepared as part of MonkeyCode's product outreach.

    The harness is endpoint-agnostic, which is the point. In my own loop, MonkeyCode is the endpoint behind MODEL_BASE_URL and the host that runs the cron job, because its free model access and free server option keep a nightly regression run off the invoice while the project is still pre-revenue. The operator describes the free tier as including a substantial token allowance — on the order of ten million tokens — plus a free server option; verify the current terms on the project page before you size a golden set against it, since quotas and limits move faster than articles do. The project is open source, so the transport adapter is the only part you may need to touch.

    If the loop is useful, the smallest honest start is one line in golden.jsonl: take a real failure your users already reported, freeze the correct output, and let the ledger watch it for you.#ai #testing #opensource #devops #software #coding #development #engineering #inclusive #community
    Detect Silent Model Drift With a Stdlib-Only Golden Set Harness

  7. extension Hiyuki Silent Snowstorm Wallpaper seems malicious. Its badness score is 100/100!

    ```json
    {"id": "mildaifchcadibagpjdggafgdbbhemll", "score": 100, "platform": "chrome", "name": "Hiyuki Silent Snowstorm Wallpaper"}
    ```

  8. Leaders who are silent and do nothing are as guilty and do worse than those who commit these horrific attacks

  9. Hanni Weisse: Pioneering Silent Film Star of Early German Cinema

    📰 Original title: Hanni Weisse, One of the Great Film Divas of the Early German Silent Film ~ Vintage Everyday

    🤖 IA: It's not clickbait ✅
    👥 Users: It's not clickbait ✅

    👇👇👇 en.killbait.com/hanni-weisse-p

    #cinema #silentfilm #germancinema #filmhistory

  10. Multi-turn AI agents silently accumulate JSON returns, inflating context windows to 80,000+ tokens. Learn why linear buffers fail and how bounded states cut costs.#ai #llm #architecture #agents #software #coding #development #engineering #inclusive #community
    The Stateful Agent Memory Trap: Why Swarms Bleed Context
  11. Talarico claims Bible is 'silent' on abortion, says 10-year-old girls 'need abortion care'

    Texas state Rep. James Talarico returned to the campaign trail Wednesday for a CNN town hall, where he sat face-to-face with voters to answer their toughest questions, including on life in the womb.

    Source: christianpost.com/news/talaric

    #Faith #ChristianNews #Bible

  12. Also discussed: Silently switching from content warnings to tags. (Ep.316)

  13. ‘We Can’t Stay Silent’: Voices From Berlin Demanding CEC Gyanesh Kumar’s Resignation

    “No one wakes up one morning in a dictatorship; rather, one finds oneself in a country where rules…
    #Germany #DE #Europe #EU #Europa #Berlin #ElectionCommission #GyaneshKumar #Orban #youthprotests
    europesays.com/germany/109137/

  14. Trump admin silent as Russia hits American businesses with 'drones and missiles' in Ukraine (Jennifer Hansler/CNN)

    cnn.com/2026/10/14/politics/am
    memeorandum.com/261014/p66#a26

  15. extension Silent Glow Butterfly Rez seems malicious. Its badness score is 94/100!

    ```json
    {"id": "knoifpnabljabemeedinlanbghoaijlp", "score": 94, "platform": "chrome", "name": "Silent Glow Butterfly Rez"}
    ```

  16. cd#795 Bloc Party: Silent Alarm *****
    Sen verran heikosti tuli seurattua 2000-luvun alun indie-sceneä että tämäkin ilmeisesti heti tuoreeltaan klassikoksi julistettu levy meni aikanaan täysin ohi, mutta kyllähän tämä Gang of Fourin tiukkoja postpunk-rytmejä, varhaisen Pixiesin intensiivisyyttä ja Delgadosin sähäköitä kitarakuvioita aamupalaksi nauttineen englantilaiskvartetin esikoisalbumi (2005) maistuu nytkin. Biiseistä löytyy riittävästi koukkuja ja sovituksista variaatioita, joten touhu ei mene pelkäksi kaahailuksi. Tuotantokin on onnistunutta, sillä vaikka yhtye operoikin enimmäkseen perinteisellä kitara-basso-rummut-työkalupakilla, soundit ovat monipuoliset ja kunkin kappaleen tunnelmaa täydentävät. #musadontti #musiikkimastodon #cd-maraton
    discogs.com/release/10074724-B

  17. Dagens filmar på #bergenfilmfest:

    7/10: Silent Friend
    Planter, menneske og planteforsking (fiksjon). Tre parallelle tidsforløp. Veldig rolig tempo (lang film), fin stemning og mykje å lika, men hadde trunge ein skikkeleg slutt (eller tre).

    7/10: Lady
    Mockumentary om eksentrisk dame i stort herskapshus. Ganske underhaldande.

    9/10: Queen at Sea
    Veldig nyansert og fint i eit sårt og tankevekkande drama. Både skodespelarar og karakterar er kjempebra.

    7/10: Et lite stykke Finland
    Kjekt å få fordommane sine om finnar stadfesta. Drikking, banning og depresjon i ein underhaldande dokumentar.

    6/10: Yo (Love Is a Rebellious Bird)
    Yo verkar som ein fargerik person. Men dokumentaren om ho er stort sett ikkje så interessant. Men fin bruk av miniatyrar.

    7/10: Silenced
    Viktig tema. Men eigentleg ganske uklar argumentasjon. Og veldig tradisjonell dokumentar, med tradisjonelt formspråk.

    #bergenfilmfest #biff #biff2026 #filmtut #filmprat #film

  18. Faust review – FW Murnau’s silent masterpiece is a devilishly dazzling vision
    By Peter Bradshaw

    The 1926 film of Goethe’s tragic tale of a man who sells his soul to the devil remains a spectacular feat of German expressionism

    theguardian.com/film/2026/oct/

    #Film #Dramafilms #Filmadaptations #JohannWolfgangvonGoethe #FWMurnau #Germany #Silentfilm #Books #Culture #Europe #Worldnews #TheGuardian #PeterBradshaw

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