← The evidence ledger
Evidence row 122596
Observed , by baseline/1.
- Kind
- listing
- About
- source_record x402_bazaar:https://tensorfeed.ai/api/premium/ai-safety/incidents/exposure
- Recorded
- Previous row
- None: the first of its kind about this subject
- Body SHA-256
- f6ddfb26290b02a784853126af2186190617d453ba21c1f40c386173f9a4201e
- Leaf
- 0x34b1380646a3eabcde2f8b6c4d6d16af923521c72110cf1bcbf7908b0dcd31e6
What was observed
{
"endpoints": [
[
"x402",
"https://tensorfeed.ai/api/premium/ai-safety/incidents/exposure"
]
],
"name": "tensorfeed.ai/api/premium/ai-safety/incidents/exposure",
"owner_address": "0x549c82e6bfc54bdae9a2073744cbc2af5d1fc6d1",
"raw": {
"accepts": [
{
"amount": "20000",
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"extra": {
"name": "USD Coin",
"resource": "https://tensorfeed.ai/api/premium/ai-safety/incidents/exposure",
"version": "2"
},
"maxTimeoutSeconds": 60,
"network": "eip155:8453",
"payTo": "0x549c82e6bfc54bdae9a2073744cbc2af5d1fc6d1",
"resource": "https://tensorfeed.ai/api/premium/ai-safety/incidents/exposure",
"scheme": "exact"
}
],
"description": "AI safety incident exposure analytics. Per-developer and per-deployer incident counts with recency-weighted exposure_score (1.0 last 30d, 0.5 days 31-90, 0.25 older), risk_domain and SEP-view (Security/Ethics/Performance) distributions, top affected artifacts. Derived over the AVID (avidml/avid-db, MIT) snapshot refreshed daily. The \"which AI vendors have the most recent reported safety incidents\" call.",
"extensions": {
"bazaar": {
"info": {
"input": {
"method": "GET",
"queryFields": {
"risk_domain": {
"example": "Security",
"type": "string"
},
"vendor": {
"example": "OpenAI",
"type": "string"
},
"within_days": {
"example": 90,
"type": "integer"
}
},
"queryParams": {
"risk_domain": "Security",
"vendor": "OpenAI",
"within_days": 90
},
"type": "http"
},
"output": {
"example": {
"billing": {
"credits_charged": 1,
"credits_remaining": 49
},
"capturedAt": "2026-05-24T12:00:00Z",
"deployers": [],
"developers": [
{
"exposure_score": 5.5,
"incident_count": 8,
"latest_report_id": "AVID-2026-R0481",
"latest_reported_date": "2026-05-18",
"recent_count_30d": 2,
"risk_domains": [
"Ethics",
"Security"
],
"role": "developer",
"vendor": "OpenAI"
}
],
"entries_count": 12,
"filter": {
"risk_domain": "Security",
"vendor": "OpenAI",
"within_days": 90
},
"ok": true,
"risk_domains": [
{
"incident_count": 8,
"recent_count_30d": 2,
"risk_domain": "Security"
}
],
"sep_view": [
{
"incident_count": 4,
"sep_view": "S0403: Adversarial Example"
}
],
"snapshot_captured_at": "2026-05-24T03:00:00Z",
"source": "avidml/avid-db",
"source_license": "MIT",
"top_artifacts": [
{
"developers": [
"OpenAI"
],
"incident_count": 3,
"name": "gpt-4o",
"type": "Model"
}
],
"window": {
"cutoff_date": "2026-02-23",
"window_days": 90
}
},
"schema": {
"properties": {
"billing": {
"properties": {
"credits_charged": {
"example": 1,
"type": "integer"
},
"credits_remaining": {
"example": 49,
"type": "integer"
}
},
"type": "object"
},
"capturedAt": {
"example": "2026-05-24T12:00:00Z",
"type": "string"
},
"deployers": {
"type": "array"
},
"developers": {
"items": {
"properties": {
"exposure_score": {
"example": 5.5,
"type": "number"
},
"incident_count": {
"example": 8,
"type": "integer"
},
"latest_report_id": {
"example": "AVID-2026-R0481",
"type": "string"
},
"latest_reported_date": {
"example": "2026-05-18",
"type": "string"
},
"recent_count_30d": {
"example": 2,
"type": "integer"
},
"risk_domains": {
"items": {
"example": "Ethics",
"type": "string"
},
"type": "array"
},
"role": {
"example": "developer",
"type": "string"
},
"vendor": {
"example": "OpenAI",
"type": "string"
}
},
"type": "object"
},
"type": "array"
},
"entries_count": {
"example": 12,
"type": "integer"
},
"filter": {
"properties": {
"risk_domain": {
"example": "Security",
"type": "string"
},
"vendor": {
"example": "OpenAI",
"type": "string"
},
"within_days": {
"example": 90,
"type": "integer"
}
},
"type": "object"
},
"ok": {
"type": "boolean"
},
"risk_domains": {
"items": {
"properties": {
"incident_count": {
"example": 8,
"type": "integer"
},
"recent_count_30d": {
"example": 2,
"type": "integer"
},
"risk_domain": {
"example": "Security",
"type": "string"
}
},
"type": "object"
},
"type": "array"
},
"sep_view": {
"items": {
"properties": {
"incident_count": {
"example": 4,
"type": "integer"
},
"sep_view": {
"example": "S0403: Adversarial Example",
"type": "string"
}
},
"type": "object"
},
"type": "array"
},
"snapshot_captured_at": {
"example": "2026-05-24T03:00:00Z",
"type": "string"
},
"source": {
"example": "avidml/avid-db",
"type": "string"
},
"source_license": {
"example": "MIT",
"type": "string"
},
"top_artifacts": {
"items": {
"properties": {
"developers": {
"items": {
"example": "OpenAI",
"type": "string"
},
"type": "array"
},
"incident_count": {
"example": 3,
"type": "integer"
},
"name": {
"example": "gpt-4o",
"type": "string"
},
"type": {
"example": "Model",
"type": "string"
}
},
"type": "object"
},
"type": "array"
},
"window": {
"properties": {
"cutoff_date": {
"example": "2026-02-23",
"type": "string"
},
"window_days": {
"example": 90,
"type": "integer"
}
},
"type": "object"
}
},
"type": "object"
},
"type": "json"
}
},
"schema": {
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"method": {
"enum": [
"GET"
],
"type": "string"
},
"queryParams": {
"properties": {
"risk_domain": {
"description": "Case-insensitive substring match against AVID risk_domains (Security, Ethics, Performance, ...).",
"type": "string"
},
"vendor": {
"description": "Case-insensitive substring match against developer + deployer + artifact name.",
"type": "string"
},
"within_days": {
"description": "Restrict to incidents reported in the last N days. Omit for full snapshot.",
"maximum": 730,
"minimum": 7,
"type": "integer"
}
},
"type": "object"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}
}
},
"lastUpdated": "2026-05-25T23:11:57.832Z",
"quality": {
"l30DaysTotalCalls": 2,
"l30DaysUniquePayers": 2,
"lastCalledAt": "2026-10-16T16:18:30.735Z"
},
"resource": "https://tensorfeed.ai/api/premium/ai-safety/incidents/exposure",
"type": "http",
"x402Version": 2
},
"source": "x402_bazaar",
"summary": "AI safety incident exposure analytics. Per-developer and per-deployer incident counts with recency-weighted exposure_score (1.0 last 30d, 0.5 days 31-90, 0.25 older), risk_domain and SEP-view (Security/Ethics/Performance) distributions, top affected artifacts. Derived over the AVID (avidml/avid-db, MIT) snapshot refreshed daily. The \"which AI vendors have the most recent reported safety incidents\" call."
}What the leaf hashes
{"body":"f6ddfb26290b02a784853126af2186190617d453ba21c1f40c386173f9a4201e","id":122596,"kind":"listing","method":"baseline/1","observed_us":1793025621808194,"prev":null,"subject":"x402_bazaar:https://tensorfeed.ai/api/premium/ai-safety/incidents/exposure","subject_kind":"source_record"}Proof
Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (296695 rows).
- 0x34b12ec8122d3aec374a7f1f1c87f845135d0dd436627483e13c6e1813f028da
- 0x4e3e2ca708c46576d3b9001f1cabe73997c8a09f008777a4a3bef1e0a31528ec
- 0x309f989bc2dc4c8849b003548f8a7fd5756bf2013cf2ccd9608f9d881014cbd9
- 0x49aae7257697343eb92ddde16b4b8390c3a6782d65e47b6c4b2936bfa654c4cd
- 0xdd762efe4d9d67c21e3162161556325643a2d135c4760bcfa9e0edb803e4f158
- 0xc78a31e559fac963f4d9aad90dda711fd6d8b937ed55b85cd76e32e6648f6842
- 0xc10d04e4fd735e53576bc49f85ad16152ad5cfb4af6651aaf72e202eb2ab9bed
- 0xd641dde0122198007109ddc36ad4b56d5079a2cd10a3e4f380db6a15e62fdfec
- 0x3537bcc0126ddadc2e072f30c37b0f6cb1dbefbeae94bf944efdd820414ab30f
- 0x852ba002507b16449e45904851c68e7f0b59aa6069ac1ae74dc557389e7c7646
- 0x5b8798d4cefad64becd1c03dfc4c9f7111db423ab06ea3f8878316222a2b26de
- 0xe57be1a98d96d75db9e9d2122794eabebfd735dea66e9d16ca63347243b3d483
- 0x08de74b7fb265ddb83e4c673da8a94e5f71829b2e6e7464c71c5138e450f2217
- 0x4338355a835617a26aa0bfcc971e84eb030d84e2aa840e3c8af958921dd080c7
- 0x610738e0c43687aded83c613c73de8b5226c73c375858a167436461c522ea213
- 0x06d71bfa7d8b41d62c8836efc2c601e1cc3772d9453596b2ae4950887f3310ca
- 0x8c756542e482157df0c36464d75c937b845e4423dbbcfad08f0cf8d5a16b9a13
- 0x20704208aa6923d6b2450ef74ede87a6e0265d46447926038fe9506e9e154b2d
- 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a
- Day root
- 0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8
- Chained
- 0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a
- Published
- On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae