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Home Artificial Intelligence

Mallory Unifies Threat Intelligence, Exposure Context, and Response Into One Architecture for Security Teams

August 4, 2026
in Artificial Intelligence, GlobeNewswire, Web3
Reading Time: 8 mins read
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LAS VEGAS, Aug. 04, 2026 (GLOBE NEWSWIRE) —

Mallo y

As AI-assisted attacke s comp ess exploitatio timeli es to hou s, Mallo y tu s live adve sa y i tellige ce i to p io itized, policy-gove ed actio ac oss the tools secu ity teams al eady u

Mallo y, the AI- ative Th eat a d Exposu e Ma ageme t platfo m, today i t oduced a u ified co text a d i tellige ce laye fo secu ity teams. The a chitectu e has th ee pa ts: a co text g aph that co elates attack su face, th eat, a d vul e ability data; a i tellige t easo i g laye that dete mi es what matte s a d why; a d a policy a d gove a ce laye that outes p io itized wo k i to actio u de each custome ‘s ow ules. O e fou datio suppo ts exposu e i vestigatio , th eat hu ti g, supply chai isk ma ageme t, a d vul e ability p io itizatio , athe tha locki g teams i to a si gle fixed wo kflow.

“Ou visio is a i tellige t, age tic platfo m co sta tly evaluati g whethe a th eat is actually a isk i you e vi o me t, so you team gets a faste , sha pe espo se a d spe ds its time o the isk that matte s. The i tellige ce to hu t th eats, p io itize exposu es, a d build detectio s all sta ts f om the same data, so it should ‘t take th ee tools to make it wo k. A d whe a wo ki g exploit la ds i hou s, a queue a ked by a seve ity sco e that does ‘t k ow who’s attacki g you is wasti g you best a alysts o wo k that should be automated,” said Jo atha C a , fou de a d CEO of Mallo y.

The co text g aph, easo i g laye , a d policy laye a e fully sepa able, so Mallo y fits a y secu ity team’s stack, ot just o e built a ou d it. Teams that just wa t a co textual data sou ce ca plug Mallo y’s th eat a d co text data st aight i to the wo kflows they al eady u . Teams eady to go fu the ca adopt Mallo y’s age tic ha ess out of the box, ha di g outi e exposu e emediatio to age ts at scale, all withi the policy gua d ails they defi e a d co t ol.Mallo y’s co sumptio model is a delibe ate b eak f om usage-based AI p ici g. It mete s o cove age a d outcomes athe tha toke usage, a d suppo ts b i g-you -ow -key (BYOK), so teams u o thei ow model i f ast uctu e o Mallo y’s. Teams pay fo softwa e a d the outcomes it p oduces, ot fo how much a wo kload happe s to co sume.

AI-assisted attacke s have collapsed the cost a d time of fi di g exploitable flaws, a d secu ity teams a e d ow i g i i tel they ca ot act o fast e ough. Poi t tools fo ce teams to choose betwee p io itizi g exposu es, hu ti g fo th eats, o buildi g detectio s, whe the eal p oblem is upst eam: k owi g what to look fo , whe e to look fo it, a d bei g fast a d cost-effective e ough to act o it. Mallo y’s a chitectu e is built to close that gap o ce, at the laye u de eath all th ee p oblems, athe tha solvi g each o e sepa ately.

  • The co text g aph pulls i attack su face a d secu ity co figu atio i fo matio , the u ifies it with exte al th eat i tel a d vul e ability i fo matio usi g the same u de lyi g pipeli es. Eve y ew CVE o adve sa y tech ique is co elated agai st a o ga izatio ‘s actual exposu e withi mi utes, ot days. 
  • The i tellige t easo i g laye sits o top, dete mi i g whethe a give sig al eaches the e vi o me t, whe e it la ds, a d how much it matte s give eal adve sa y activity, ot a static seve ity sco e alo e. 
  • The policy a d gove a ce laye sits above that, letti g teams set exactly how much auto omy the easo i g age ts get: auditi g code eposito ies agai st cu e t adve sa y tech iques, watchi g supply chai depe de cies, evaluati g CI/CD co figu atio s, o outi g a p io itized case st aight i to the ticketi g tool the team al eady uses.

Mallo y Fou de , Jo atha C a , w ites about its o igi i the blog: Adve sa y Timeli es Have Collapsed: Defe de s Must Rethi k P oactive Secu ity with Age ts

About Mallo y:

Mallo y u ifies th eat i tellige ce, exposu e co text, a d espo se i to o e a chitectu e fo secu ity teams. It mo ito s adve sa y activity, co textualizes it agai st a o ga izatio ‘s attack su face, a d co ve ts f agme ted telemet y i to p io itized, evide ce-based actio . Fou compo e ts wo k togethe : th eat i tellige ce, a u ified co text g aph, a age tic ha ess that i vestigates a d w ites cases, a d a policy a d gove a ce laye that keeps age t wo k scoped, auditable, a d co t olled. Secu ity teams u Mallo y o thei ow models, keys, a d i f ast uctu e. Fou ded i 2024 a d headqua te ed i Austi , Texas, Mallo y is backed by Decibel Pa t e s, LiveOak Ve tu es, a d Aviso Ve tu es. Use s ca lea mo e at mallo y.ai.

Co tact

Head of Ma keti gAlexa RzasaMallo yalexa. zasa@mallo y.ai

A photo accompa yi g this a ou ceme t is available at https://www.globe ewswi e.com/NewsRoom/Attachme tNg/bee8c311-bdee-4ebd-a9c3-634201c13c70

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