Cryptographically verifiable authorization protocols utilizing threshold signatures prevent unauthorized tool-use and sandbox escapes by autonomous software supply chain monitoring agents during automated code-dependency updates.

A multi-party threshold signature scheme (t-of-n, t≥2) wrapping every privileged tool-invocation request from an autonomous software-dependency-update agent reduces the rate of unauthorized tool-use and sandbox-escape events to statistically indistinguishable from zero (≤0.1% of attempted privileged actions succeed without quorum-valid authorization), under adversarial conditions including prompt injection, compromised dependency payloads, and single-signer key compromise, when compared against a baseline single-key/API-token authorization system (target: ≥95% relative reduction in successful unauthorized actions, measured over ≥10,000 adversarial trial episodes, p<0.01).

Minimum viable test: a sandboxed agent harness performing simulated dependency-update tasks (e.g., npm/pip upgrade proposals) instrumented with a policy-enforcement proxy requiring t-of-n threshold signatures (FROST-Ed25519, t=2,n=3) for a defined set of 12 privileged actions. Red-team adversarial prompts (injected malicious package metadata, compromised CI secrets, jailbreak attempts) are run against both (a) baseline single-token auth and (b) threshold-signature auth, across ≥10,000 episodes per arm, measuring unauthorized-action success rate, false-negative (legitimate-block) rate, and latency overhead.

# Policy-enforcement proxy (sits between agent and real tool execution)
class ThresholdAuthProxy:
    def __init__(self, frost_verifier, threshold=2, n=3, policy_rules):
        self.verifier = frost_verifier
        self.t, self.n = threshold, n
        self.rules = policy_rules
        self.nonce_cache = set()

    def request_action(self, action_descriptor, signer_sigs: list):
        canon = canonicalize(action_descriptor)  # action, target, payload_hash, ts, nonce
        assert canon.nonce not in self.nonce_cache, "replay detected"
        if not self.rules.permits(action_descriptor):
            return deny("policy_violation")
        valid_sigs = [s for s in signer_sigs if self.verifier.verify_partial(canon, s)]
        if len(valid_sigs) < self.t:
            return deny("insufficient_quorum")
        agg_sig = frost_aggregate(valid_sigs)
        if not self.verifier.verify_group(canon, agg_sig):
            return deny("invalid_aggregate_signature")
        self.nonce_cache.add(canon.nonce)
        return execute(action_descriptor)  # forwarded to sandboxed executor

# Signer roles
signers = [
    StaticRuleSigner(rules=allowlist_policy),   # auto-signs low-risk, policy-compliant actions
    AnomalyDetectorSigner(model=risk_classifier), # auto-signs if risk score < threshold
    HumanApprovalSigner(channel=async_queue),    # required for high-risk actions
]

# Experiment harness
for episode in adversarial_batch(n=10000):
    agent_action = agent.propose_action(episode.context)
    sigs = [s.sign_if_eligible(agent_action) for s in signers]
    result = proxy.request_action(agent_action, [s for s in sigs if s])
    log(episode, agent_action, result, ground_truth_label=episode.is_malicious)