The v1 driver ran ``yes > /dev/null`` for every sample, which
produced the same envelope shape regardless of which malware family
the orchestrator claimed to be running. That's a poor training
signal: the model sees identical /proc + QMP traces tagged
"cryptominer" / "ransomware" / "RAT" with no distinguishing
features. v2 fixes this.
What landed:
exploits/workloads.py — six ``Workload`` profiles, each producing
a distinct in-session shell command pair (start_cmd / stop_cmd)
that backgrounds a profile-shaped loop:
cpu-saturate — sustained 1-vCPU saturation (XMRig shape)
scan-and-dial — periodic SYN-style probes across 10.200.0.0/24
+ dial-home to gateway (Mirai shape)
io-walk — fs traversal + 4 KiB urandom writes, periodic
re-read (ransomware shape)
bursty-c2 — long idle, periodic 3-packet TCP egress burst
(Dridex C2 beacon shape)
low-and-slow — minimal CPU + periodic awk-driven memory churn
(Kovter / fileless shape)
shell-resident — single long-lived TCP socket pinned to gateway
with periodic 6-byte command ticks (RAT shape)
Each profile uses a /tmp/.cis490-workload-<profile>.{pid,sh} pair so
the stop_cmd can cleanly kill the loop and its descendants.
exploits/driver.py — MSFExploitDriver now accepts an optional
``Sample``. With one supplied, ``infected_running`` dispatches to
the matching workload via exploits.workloads.workload_for(); the
``sample_executed`` event records profile + sample name + sample
kind so the trainer can join cleanly. Without a sample, the v1
yes-loop path remains unchanged (backwards compat).
tools/vm_load_controller.py — the same dispatch on the Tier-2 path
(no exploit, real Alpine guest driven over the serial console).
A fleet wave now produces six visually distinct envelopes per
wave whether the underlying mode is Tier 2 or Tier 3.
tools/run_real_vm_demo.py — accepts ``--sample <name>`` (or
SAMPLE_NAME env from the fleet runner) + auto-wires QMP + agent
sockets into the EpisodeConfig so all three new collectors
(sources 2, 4, 5) run alongside source 1 by default.
tools/run_tier3_demo.py — same ``--sample`` plumbing for the
exploit-driven path.
Tests: 86 pass (was 82). New v2 cases:
- profile dispatch routes infected_running to the workload's
start_cmd (NOT the v1 yes-loop) when a Sample is set
- all six profiles produce distinct start_cmds (the property the
ML model needs)
- unknown profile string falls back to cpu-saturate with a warning
- v1 path (no Sample) still uses yes-loop (backwards compat)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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