Computer Virus
Benchmark: Windows PE file-infecting virus executing on a generic host OS; scope is one instantiated digital “body,” not the botnet/population.
In a nutshell
22-28
Emergent Category
The virus shows regular, host-dependent replication (4.1/4.2), non-zero information handling, but no intrinsic metabolism; its behavior and persistence are scaffold-locked to the host OS/hardware, which matches Tier 2.
Score Drivers
Which elements were responsible for increasing the score
- Host micro-niche construction (5.3 = 66): Disables defenses / installs persistence keys that recursively benefit the same lineage on that host across runs.
- Non-trivial structure & blueprint (1.1 = 33, 1.2 = 33): Encapsulated modules plus a self-contained compiled blueprint raise baseline complexity above zero, but are capped by Digital Blueprint/Morphology guards.
Score Draggers
Which elements were responsible for keeping the score low
'Care' Snapshot (i.e., measure of consciousness)
The virus exhibits externally anchored care: it “cares” to persist and reproduce only within a host-provided substrate. Its actions (infection, persistence, evasion) are reactive and rule-bound, lacking an endogenous agenda or self-maintenance loops typical of higher tiers. (Tier 2 framing per rubric output rules.)
Types of change tracked
(determined by observed change-avoidance behavior)
- Basic threats: Responds to immediate removal/detection by hiding/branching (e.g., skip if debugger/AV found), but cannot repair itself if body is damaged.
- Resource clues: Scans for exploitable file types/locations (PE headers, autoruns); reacts when found.
- Invaders/antagonists: Disables host defenses or alters registry/services; these are host-level effects, not internal immune-like repair.
Typical time duration of change-tracked
(determined by observed behavior and associated cause-and-effect time-lags)
- Seconds–minutes: Event-triggered execution, scanning, and infection pipelines within a single run.
- Hours–days: Persistence on a host via autoruns/services until removal.
Deep-dive into Life scoring
We use eight metrics that cover (and go beyond) classic traits of life
1. Structural & genetic complexity (22% of overall score): complexity in physical form (morphology) and genomic organization
Morphological Differentiation (50%)
Does the system exhibit specialized body structures or multiple cell types indicating advanced morphology?
33.
Encapsulated modules (e.g., decryptor/packer, infection engine, payload branch) exist inside a fixed codebase, meeting 33 for non-trivial internal structure. No autonomous self-re-wiring or creation of new top-level modules at runtime, so <66.
Why not lower? Modules are concurrent and separable, not a monolithic script.
Why not higher? No self-assembled architectural novelty; digital morphology guard caps at ≤33 absent self-reorganization.
Genome complexity (50%)
How complex and multi-layered is the organism’s genetic architecture and information-processing genome?
33.
The compiled binary functions as a self-contained digital blueprint (meets 33 per Digital Blueprint Guard). It cannot autonomously instantiate/verify/update without host loaders/integrity scaffolds, so >33 is barred; GENOME–PHENOTYPE synergy also blocks 100 since 1.1<66.
Why not lower? There is a genuine, self-contained specification.
Why not higher? Reliance on external loaders/updates caps at 33.
2. Autonomy (18% of overall score): self-regulation without external micromanagement
Internal Feedback Loops (40%)
Does the system regulate internal behavior through feedback pathways that affect future states or activity?
0.
Behavior is trigger-locked to host events with no durable, cross-domain internal modulation; virus is an explicit 0-tier exemplar.
Why not lower? Already at 0.
Why not higher? No nested, persistent internal state altering multi-domain behavior.
Error Correction / Self-Regulation (35%)
Can the system detect and correct internal deviations to preserve its function?
33.
Basic checks (e.g., “don’t reinfect”, simple integrity/gating) avoid immediate self-sabotage within a run, which matches minimal regulation.
Why not lower? There is some intrinsic gating that modulates actions.
Why not higher? No self-healing/rollback that restores baseline across sessions; no internal redundancy or repair memory
Decoupling from External Control (25%)
To what extent can the system operate without moment-to-moment external triggering?
33.
Activity occurs only when external triggers launch the process (user run, autostart), exactly the 33 tier (“only active when specific external triggers are present”).
Why not lower? After launch, it can proceed for a while without continuous new pokes.
Why not higher? Fails the Digital Endogenous Agenda Guard — no self-generated, multi-behavior agenda; 66+ requires an internal agenda spanning behaviors without external prompting.
3. Boundary Coherence (10% of overall score): Persistence of identity and separation from surroundings
Integrity Under Perturbation (40%)
How well does the system maintain functional identity when stressed?
0.
Loss/corruption of code collapses function; no autonomous re-assembly of major structures.
Why not lower? Already at 0.
Why not higher? No structural regeneration; Emergent Boundary Rule forbids crediting host repair.
Input Filtering (35%)
Can it distinguish meaningful signals from environmental noise?
33.
Fixed rule-based gating (e.g., file-type checks, skip already-marked files) filters inputs at a basic level.
Why not lower? Real, encoded gates exist.
Why not higher? No multi-modal hierarchy or adaptive, context-aware suppression; simple rules only.
Structural Persistence (25%)
How well does the system resist degradation or maintain form across time or perturbation?
33.
The digital body (binary) persists and loads consistently if intact, meeting passive persistence.
Why not lower? It is a stable, re-loadable structure.
Why not higher? No autonomous rebuild after damage; persistence relies on host scaffolds.
4. Reproduction (12% of overall score): Logic for generating viable new copies or offspring
Full Self-Replication (50%)
Can it independently recreate a complete, viable version of itself?
33
Within a host environment, it copies/installs itself into new files — a host-bound analogue of viral replication.
Why not lower? Actual self-multiplication occurs in-situ.
Why not higher? Cannot provision substrate or replicate independent of host; environmental provisioning guard blocks ≥66.
Reproductive Boundary Logic (35%)
Does the system coordinate or gate reproduction using internal boundary logic?
33.
Encoded gates (file-type/“already infected” checks) restrain replication.
Why not lower? There is bona-fide reproductive gating.
Why not higher? Checks are single/few-signal and stimulus-locked; no multi-signal integration (e.g., density/resource/time) to qualify for 66.
Partial Reproduction (15%)
Can some parts regrow the whole or initiate reproduction?
0.
No budding/fragment-regeneration analogue; fragments aren’t viable new units.
Why not lower? Already at 0.
Why not higher? No structural pathway from part → whole.
5. Evolvability (10% of overall score): Feedback-driven structural change across generations
Structural Variation (40% of evolvability)
How much inter-individual or internal variation exists structurally?
33.
Polymorphic mutation produces code variants across infections.
Why not lower? Variation is genuine and lineage-relevant.
Why not higher? Does not manifest as body-plan plasticity or multi-system phenotypes.
Adaptive Feedback (35%)
Does the system incorporate environmental information into future structure or behavior?
33.
One-way adjustments (e.g., debugger-aware branching) alter immediate behavior within runs.
Why not lower? There is run-bound adaptation.
Why not higher? No durable, internally managed learning across contexts; external C2 updates don’t count.
Environmental Shaping (25%)
Does the entity alter its environment in ways that extend or reinforce its survival?
66.
It remodels the local host niche (disable defenses, persistence hooks) such that future runs of the same lineage on that host are advantaged.
Why not lower? Changes persist and feed back to viability on that machine.
Why not higher? Does not reshape ecosystem-level selective landscapes across unrelated species.
6. Metabolism (10% of overall score): Energy transformation and entropy management
Energy Transformation Capability (50%)
Can the system extract, convert, and use energy?
0.
Consumes host CPU/power with no autonomous acquisition/regulation.
Why not lower? Already 0.
Why not higher? Digital Host-Energy hard cap applies.
Waste / Entropy Management (25%)
Does the system handle byproducts to avoid collapse?
0.
No intrinsic excretion/recycling; host OS handles resources.
Why not lower? Already 0.
Why not higher? Host management cannot lift the entity’s score.
Maintenance of Internal Gradients (25%)
Does it preserve different conditions internally to sustain function?
0.
No self-maintained compartments/gradients.
Why not lower? Already 0.
Why not higher? Computation state ≠biochemical gradients; no pumps/compartments.
7. Individuality (10% of overall score): Functional unity and internal modular coordination
Boundary Unity (50%)
Is there clear coherence and closure of the system boundary?
33.
A contiguous digital body (process/binary) is isolatable as a unit.
Why not lower? Clear, identifiable boundary.
Why not higher? Depends on host containment; no self-managed multilayer boundary.
Separation from Collectives (30%)
Does it function meaningfully apart from its group?
0.
No viability outside host computing environment; obligate dependence.
Why not lower? Already 0.
Why not higher? Cannot complete any life-cycle analogue on generic substrates.
Internal Coordination (20%)
Does it coordinate between parts to maintain overall behavior?
33.
Reflex-like module pipeline (scan → infect → hide) exhibits minimal intra-module ordering.
Why not lower? There is basic sequencing beyond a single reaction.
Why not higher? No hierarchical meta-controller or dynamic cross-modulation across modules.
8. Information Handling (8% of overall score): Storage and processing of state-linked signals
Signal Processing (40%)
Does it transform or evaluate incoming signals?
33.
Branching on host signals (file type, AV presence) meets basic processing.
Why not lower? Multiple conditional gates affect behavior.
Why not higher? No multi-signal, model-based inference that generalizes across domains.
Signal Encoding (30%)
Can it represent information in structured internal form?
0.
The code encodes itself (blueprint) rather than environmental models; durable “experience” is not structurally stored within the entity.
Why not lower? Already 0.
Why not higher? Blueprint ≠signal memory; scaffold-bound flags don’t qualify as intrinsic encoding.
Feedback-Linked Behavior (30%)
Is behavior altered in a sustained way by past signal exposure?
33.
Prior exposure can toggle in-run behavior (e.g., skip reinfection if a flag exists), meeting short-term feedback.
Why not lower? Real, state-contingent behavior occurs.
Why not higher? No cross-context plasticity encoded within the entity itself; scaffold-bound adaptations remain ≤33.